Assistant Vice President - Principal Engineer

AVP, Principal Software Engineer (Senior Technical lead)

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Data & ML Architect

Staff Advanced Quality Engineer (Software)

Responsibilities: <ul><li>Lead the design and architect solutions that meet SYF business requirements to deliver business value by enabling rapid innovation through modern software development practices and product delivery through rapid innovation and continuous integration. In-depth knowledge of credit application and web application platforms.</li><li>Perform Technology Alternate Assessment, create Proof-of-Concept (as necessary) Provides guidance and direction to product teams to ensure compliance with the standards and best practices Work collaboratively with Product Management and Platform Engineering teams during development, launch and continuing refinement of products iteratively</li><li>Lead Agile sprints as the technical expert, including sprint planning, daily standups, backlog grooming sessions, and sprint reviews Influence and collaborate with software developers, UX designers, product managers, application architects, and customer application experts to create high performing and reliable application components.</li><li>Work with third party vendors to develop software and/or integrate their software into the companys products</li><li>Drive a CI/CD strategy using our Jenkins, Bitbucket, and uDeploy stack.</li><li>Maintain deep hands-on technical knowledge of evaluating trends in modern software development practices.</li></ul> Requirements: <ul><li>Bachelor’s degree and a minimum 7 years of experience with software engineering OR, in lieu of degree 9 years of experience with software engineering.</li><li>5+ years of applied Java experience</li><li>5+ years of hands-on experience in Credit Card Acquisition platform with ample knowledge in credit card application processing and decisioning systems.</li><li>Experience in Front End UI (JavaScript/Typescript) development and Backend Java programming.</li><li>Critical Thinking, creativity and problem-solving skills.</li><li>Strong analytical and problem-solving skills.</li><li>Excellence in technical communication with technical and non-technical peers.</li><li>Basic understanding of Artificial Intelligence.</li></ul>

Responsibilities: <ul><li>Lead the development effort for cloud-native applications across the Caching Solutions and Rewards System teams, ensuring timely execution against committed business outcomes.</li><li>Drive business commitments by aligning scope, sequencing, and technical approach with Product Management, and ensuring delivery plans are realistic, transparent, and measurable.</li><li>Design and implement continuous integration and continuous delivery (CI/CD) processes to deliver applications to production, fostering a culture of continuous process improvement.</li><li>Provide hands-on technical leadership through architecture/design reviews, code reviews, and guidance to engineers to ensure compliance with standards and best practices.</li><li>Perform Technology Alternate Assessments and create Proofs-of-Concept (as necessary) to validate options and inform technical decisions.</li><li>Work collaboratively with Product Management and Platform Engineering teams during development, launch, and continuing refinement of products iteratively.</li><li>Collaborate with internal technical resources and third-party vendors to resolve issues, understand</li><li>underlying causes, and implement sustainable solutions.</li><li>Work with team members to design, architect, and implement solutions across geographic locations, ensuring effective coordination and consistent engineering execution.</li><li>Coordinate and communicate status across stakeholders, and report delivery progress, risks, and dependency needs to leadership on a regular cadence.</li><li>Maintain deep hands-on technical knowledge by evaluating trends in modern software development practices; continuously learn and stay at the leading edge of industry trends.</li></ul> Requirements: <ul><li>Bachelor’s Degree with 8+ years of system engineering experience, or in lieu of a degree 10+ years of skilled system engineering experience.</li><li>8+ years of Strong hands-on development experience in Java and Spring Boot for building enterprise-grade services.</li><li>5+ years of Proven expertise in designing and implementing cloud-native applications using a microservices-based architecture.</li><li>Solid knowledge of event streaming and processing patterns using Kafka.</li><li>Experience deploying and operating applications on cloud platforms such as AWS and PCF (Pivotal Cloud Foundry).</li><li>Strong understanding of data storage and caching concepts and implementations using GemFire, Redis &amp; Elastic cache.</li><li>5+ years of Working knowledge of database design and persistence using MySQL, Aurora SQL &amp; no SQL.</li><li>Experience with observability, logging, and production monitoring, including tools such as Splunk and New Relic</li></ul>

Responsibilities: Software Development: <ul><li>Design, develop, test, and maintain scalable software applications using Java Spring Boot and JavaScript for backend and frontend development, respectively. Build clean, reusable, maintainable, and well-tested code following software engineering best practices.</li></ul> Full Stack Application Development: <ul><li>Develop end-to-end web and mobile applications using Java Spring Boot, React or React Native, backend APIs, database integrations, and modern UI frameworks to deliver intuitive user experiences.</li><li>Design and develop secure RESTful APIs, backend services, authentication mechanisms, and data access layers while ensuring application scalability and performance.</li></ul> AI Enable Engineering: <ul><li>Leverage AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, Amazon Q, or similar tools to improve engineering productivity.</li><li>Experience integrating LLM APIs or AI-powered capabilities into applications is desirable.</li></ul> Collabration: <ul><li>Collaborate with Product Managers, Business Analysts, UX Designers, QA Engineers, Architects, and cross-functional engineering teams to understand business requirements and deliver scalable software solutions.</li><li>Participate in sprint planning, technical discussions, estimation, backlog refinement, and Agile ceremonies.</li></ul> Testing &amp; Quality: <ul><li>Develop unit tests, integration tests, and participate in peer code reviews to ensure software quality, maintainability, reliability, and performance.</li><li>Follow secure coding standards and engineering best practices.</li></ul> Cloud &amp; Devops: <ul><li>Contribute to CI/CD pipelines and cloud-native application deployments using technologies such as Docker, Kubernetes, Azure, AWS, GitHub Actions, or Azure DevOps.</li></ul> Continous Improvement: <ul><li>Identify opportunities to improve software architecture, engineering standards, automation, developer productivity, and application performance.</li><li>Adopt AI-assisted engineering workflows and modern software development practices.</li></ul> Technical Support: <ul><li>Troubleshoot production issues, perform root cause analysis, and resolve application issues while ensuring minimal business disruption.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).</li><li>3–5 years of professional software development experience.</li><li>Minimum 3+ years of hands-on full-stack development experience.</li><li>Experience developing production-grade web or mobile applications (not academic or personal projects).</li><li>Strong proficiency in Java Spring Boot and JavaScript.</li><li>Experience developing applications using React or React Native.</li><li>Experience developing backend services using Node.js or equivalent backend technologies.</li><li>Strong understanding of REST API development.</li><li>Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or equivalent.</li><li>Strong knowledge of Git and modern software engineering practices.</li><li>Experience working in Agile/Scrum teams.</li><li>Strong understanding of object-oriented programming, software design principles, and data structures.</li></ul>

Responsibilities: <ul><li>Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.</li><li>Develop and maintain the entire DevOps pipelines.</li><li>Ensure seamless deployment and integration between cloud/prem environments (AWS).</li><li>Integrate AI models into production environments using containerized platforms such as OpenShift.</li><li>Implement and maintain network security protocols to safeguard AI systems and data pipelines.</li><li>Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.</li><li>Monitor and optimize system performance, reliability, and scalability.</li><li>Support CI/CD processes and infrastructure for AI model deployment and updates.</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related field.</li><li>Bash and Unix/Linux command-line toolkit is a must-have.</li><li>Deep technical background, with hands-on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA workflow, and Confluence).</li><li>Hands-on experience with OpenShift, Docker, Kubernetes.</li><li>Knowledge of cloud platforms (e.g. AWS) is a must-have.</li><li>Exposure to data and network security and compliance in AI systems.</li><li>Knowledge of API integration and microservices architecture.</li><li>Proficiency in Python used both for automation and ML-related tasks</li><li>Knowledge of Workflow Orchestrator, such as Ctrl-M</li><li>Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos.</li><li>Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, Open Telemetry.</li><li>Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.</li></ul>

Responsibilities: People, Talent and Cross-Functional Collaboration:&nbsp; <ul><li>Ensure optimal staffing levels across front-end, back-end, full-stack, and platform specializations.&nbsp;</li><li>Hire, coach, and develop top-tier engineering talent.</li><li>Manage direct reports and technical leads, address performance issues promptly, and build strong relationships with Product, Design, Platform, Data, and agile train leadership to deliver cohesive, customer-focused solutions.</li><li>Community of Practice, Developer Experience and AI-Driven Engineering: As AI tooling becomes inseparable from modern engineering practice, own the convergence of Community of Practice standards and AI adoption as a single discipline.&nbsp;</li><li>Foster best practice adoption across the engineering community with AI tooling treated as a first-class part of the practice.</li><li>Define standards for responsible AI adoption — including when to use AI coding assistants, agents, skills, and MCP integrations versus traditional approaches.</li><li>Establish clear guidance on the distinction between AI Skills (deterministic capabilities) and Agents (autonomous, multi-step workflows). </li><li>Evaluate, pilot, and roll out AI tools (GitHub Copilot, Claude Code, Cursor, Windsurf, Continue.dev, Aider, Cline, Ollama). </li><li>Define governance for AI use in regulated financial services contexts including data handling, PII protection, IP compliance, and code provenance. </li><li>Track and measure the combined impact of CoP practices and AI adoption on cycle time, PR throughput, defect rates, and developer satisfaction.</li><li>System Architecture and Technical Direction: Own a modern view of system architecture spanning client, server, data, integration, and AI layers.&nbsp;</li><li>Champion patterns such as micro-frontends, BFF, event-driven, API-first, serverless, and composable architectures.&nbsp;</li><li>Partner with Enterprise Architects on platform alignment.&nbsp;</li><li>Guide trade-off decisions (monolith vs. microservices, sync vs. async, build vs. buy). Use AI-powered architecture tools to accelerate design exploration and generate ADRs.</li><li>Ensure teams document decisions so both humans and AI agents can reason about the system. </li><li>Understand how AI tools interact with system architecture — including RAG, vector databases, MCP integrations, and agentic workflows.</li></ul> Strategic Planning, Delivery and Operational Excellence:&nbsp; <ul><li>Ensure plans align with CoP goals, review quarterly commitments to flag risks early, and step in to resolve conflicts between product, design, and engineering.&nbsp;</li><li>Drive CI/CD best practices, ensure high-quality scalable solutions across the stack, and provide on-call support during escalations.&nbsp;</li><li>Support tech leads hands-on when needed, regardless of which layer of the stack the problem lives in.</li></ul> Requirements: <ul><li>Strong hands-on background in modern front-end technologies (ReactJS, TypeScript, NextJS, Cypress) as an anchor foundation, with working knowledge of back-end technologies, APIs, microservices, and data layer concepts.&nbsp;</li><li>Experience with AWS cloud services, CI/CD pipelines, and modern DevOps practices.&nbsp;</li><li>Proven ability to lead engineers working across the full stack.</li><li>Solid grounding in system architecture fundamentals — distributed systems, scalability, CAP trade-offs, caching, messaging, API design — and familiarity with modern patterns (micro-frontends, BFF, event-driven, CQRS, serverless, composable architectures).&nbsp;</li><li>Experience making and documenting architecture decisions (ADRs), with understanding of how AI-native architecture (RAG pipelines, vector databases, agent orchestration) differs from traditional architecture.</li><li>Hands-on experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) with clear understanding of the difference between AI Skills and Agents, familiarity with MCP (Model Context Protocol), RAG patterns, and experience defining AI usage guidelines and governance frameworks for regulated environments.&nbsp;</li><li>Awareness of the open-source AI tooling ecosystem (Continue.dev, Aider, Cline, Ollama).</li><li>Proven experience leading and growing high-performing engineering teams, running or contributing to a Community of Practice, and strong communication skills with the ability to influence across organizational levels.</li></ul>

Role Description: <ul><li>We are seeking an experienced Lead Quality Automation Engineer to join our growing Quality Engineering practice in Leeds.&nbsp;</li><li>This role is suited to a highly technical Quality Engineer who enjoys solving complex engineering challenges while working directly with clients across multiple industries.&nbsp;</li><li>You will play a key role in designing automation solutions, driving engineering best practices, mentoring team members, and helping organisations modernise their quality engineering capabilities.&nbsp;</li><li>As a Lead Quality Automation Engineer, you will remain hands-on with automation development while providing technical leadership across delivery teams.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Design, develop and maintain scalable automated testing frameworks for enterprise applications.&nbsp;&nbsp;</li><li>Deliver high-quality automation solutions using modern testing tools and object-oriented programming languages.&nbsp;&nbsp;</li><li>Work collaboratively with software engineers, architects, product owners, and business stakeholders throughout the software development lifecycle.&nbsp;&nbsp;</li><li>Champion Shift-Left Quality Engineering practices by embedding testing early in the development process.&nbsp;&nbsp;</li><li>Analyse application source code to identify defects, improve test coverage, and support overall software quality.&nbsp;&nbsp;</li><li>Contribute to Continuous Integration and Continuous Delivery (CI/CD) pipelines to enable efficient automated testing.&nbsp;&nbsp;</li><li>Apply AI-assisted engineering tools and Generative AI technologies to improve testing efficiency and engineering productivity.&nbsp;&nbsp;</li><li>Provide technical leadership, mentoring, and guidance to junior engineers and project teams.&nbsp;&nbsp;</li><li>Support clients in adopting modern Quality Engineering practices and continuous improvement initiatives.&nbsp;&nbsp;</li><li>Participate in technical discussions, solution design, and engineering governance activities.&nbsp;&nbsp;</li></ul> Requirements: <ul><li>Proven experience in Quality Engineering and Test Automation within enterprise environments.&nbsp;&nbsp;</li><li>Hands-on experience developing and maintaining automation frameworks.&nbsp;&nbsp;</li><li>Strong programming experience in one or more object-oriented languages such as Java, Python, C#, JavaScript, or TypeScript.&nbsp;&nbsp;</li><li>Experience with modern automation frameworks such as Playwright, Selenium, or equivalent.&nbsp;&nbsp;</li><li>Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform.&nbsp;&nbsp;</li><li>Good understanding of Continuous Integration and Continuous Delivery (CI/CD) principles.&nbsp;&nbsp;</li><li>Experience working with AI productivity tools such as GitHub Copilot, Claude, or similar technologies.&nbsp;&nbsp;</li><li>Strong understanding of software development lifecycle (SDLC) and Shift-Left Testing methodologies.&nbsp;&nbsp;</li><li>Excellent communication and stakeholder management skills with the ability to work directly with clients.&nbsp;&nbsp;</li><li>Demonstrated ability to work independently while managing multiple priorities.&nbsp;&nbsp;</li></ul> Preferred Qualifications&nbsp; <ul><li>Commercial experience implementing Generative AI solutions within Quality Engineering.&nbsp;&nbsp;</li><li>Experience working within consulting or professional services organisations.&nbsp;&nbsp;</li><li>Knowledge of Agentic AI concepts.&nbsp;&nbsp;</li><li>Familiarity with LangChain and LangGraph.&nbsp;&nbsp;</li><li>Experience mentoring engineers and providing technical leadership.&nbsp;&nbsp;</li><li>Exposure to both public and private sector projects.&nbsp;&nbsp;</li></ul> Personal Attributes&nbsp; The successful candidate will demonstrate:&nbsp; <ul><li>Strong analytical and problem-solving skills.&nbsp;&nbsp;</li><li>Excellent verbal and written communication abilities.&nbsp;&nbsp;</li><li>Adaptability in fast-paced consulting environments.&nbsp;&nbsp;</li><li>A continuous learning mindset with evidence of ongoing professional development.&nbsp;&nbsp;</li><li>A collaborative approach with the ability to influence technical and non-technical stakeholders.&nbsp;&nbsp;</li></ul> Working Arrangement&nbsp; <ul><li>This role follows a hybrid working model with an expectation of approximately two to three days per week onsite, depending on client requirements.&nbsp;</li><li>Some travel to client locations may be required.&nbsp;</li></ul> Security Requirements&nbsp; <ul><li>Candidates must either hold Security Clearance (SC) or be eligible to obtain SC Clearance in accordance with UK Government requirements.&nbsp;</li></ul>

Role Description: <ul><li>The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.</li><li>The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact.&nbsp;</li><li>The individual is expected to work in close partnership with our client IT team, to leverage existing AI &amp; data capabilities on Databricks &amp; AWS (where applicable) while developing solutions.</li></ul> Responsibilities: Strategic problem solving and driving cross-functional execution&nbsp; <ul><li>Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation</li><li>Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&amp;L owners</li><li>Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace</li></ul> Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions&nbsp; <ul><li>Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)</li><li>Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes</li></ul> Executing rapid AI-augmented research and competitive intelligence&nbsp; <ul><li>Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights</li><li>Synthesize structured datasets (S&amp;P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs</li></ul> Support strategy team in day-to-day execution by leveraging AI-led tools <ul><li>Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling</li><li>Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&amp;Ls, pricing</li><li>Support M&amp;A pipeline by AI-screening targets and generating investment theses</li></ul> AI enablement, coaching and continuous innovation <ul><li>Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution</li><li>Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users</li><li>Stay current on agentic stacks, multimodal models, and deep research agents</li></ul> Requirements: Skillset and capabilities AI fluency and hands-on deployment orientation&nbsp; <ul><li>Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.</li><li>Proven ability to convert business problems into reusable AI workflows, tools, or accelerators</li><li>Builder mindset with experience prototyping AI solutions using frontier tools &amp; low-code platforms</li></ul> Analytics, modelling, and research excellence <ul><li>Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.</li><li>Ability to synthesize structured datasets with unstructured sources</li><li>Research discipline – source triangulation and rigorous validation of AI outputs</li></ul> Strategic problem solving, communication, executive presence, and influence&nbsp; <ul><li>Sharp "so-what" orientation to translate AI outputs into practical executive decisions</li><li>Crisp written and verbal communication, with ability to frame board-ready narratives</li><li>Skill in explaining AI workflows and implications to both technical and non-technical audiences</li><li>Stakeholder management across strategy, commercial, data, and technology teams</li></ul> Ownership, and execution <ul><li>Independently own workstreams end-to-end – from framing through deployment</li><li>High bar for quality; never publishes unchecked AI outputs or unvalidated analysis</li></ul> Coaching and capability building&nbsp; <ul><li>Patience and ability to coach colleagues on prompting, research workflows, and source validation</li><li>Track record of building reusable playbooks – templates and training modules that scale adoption</li></ul> Passion, curiosity, and learning agility <ul><li>Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools</li><li>Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability</li></ul> Qualifications:&nbsp; <ul><li>BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.</li><li>3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.</li><li>Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.</li><li>Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.</li><li>Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.</li><li>Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.</li><li>Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.</li><li>Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage</li></ul>

Responsibilities: Application Development &amp; Delivery: <ul><li>Lead development and implementation Cards related applications with overall accountability ensuring product deliveries are timely and with good quality.</li><li>Partner with System Analyst &amp; subject matter experts to understand and implement functional and technical requirements</li><li>Provide systems input to specification phase (e.g., effort estimates, high-level delivery plan) based on impact assessment (e.g., function points)</li><li>Partner with Architects, Security and System Analysts to ensure solution design complies with enterprise design principles, security and control standards. Have a hands-on approach to ensure that the application teams build the enhancements according to the solution plan</li><li>Drive platform modernization initiatives in collaboration with Architecture, Risk, and Infrastructure teams.</li><li>Partner with Test Manager to ensure completion of SIT, UAT, performance / load testing and application security testing with quality results</li><li>Work with Security to facilitate completion of penetration testing and remediation of findings in accordance with Mitigation Plan</li><li>Prepare and manage technical implementation plan across application teams</li><li>Coordinate technical implementation activities across application teams to ensure non-event production cutover and adequate post implementation support</li><li>Escalate issues that impact project schedule on timely basis and propose workarounds/resolutions</li><li>Work with vendor to ensure product deliveries are timely and of good quality.</li><li>Manage budgets coming from different projects.</li><li>Ensure project documentation is done up in accordance with bank standards</li></ul> DevOps &amp; Technical Governance: <ul><li>Champion CI/CD, automated testing, and infrastructure-as-code practices.</li><li>Ensure compliance with patching, vulnerability remediation, and security standards.</li><li>Manage deployments and change control processes.</li></ul> Incident &amp; Problem Management: <ul><li>Provide technical leadership during major incidents.</li><li>Conduct root cause analysis and implement preventive actions.</li><li>Collaborate with support teams for smooth production transitions.</li></ul> Team &amp; Stakeholder Management: <ul><li>Lead high-performing teams across onshore and offshore locations.</li><li>Mentor team members and foster technical excellence.</li><li>Collaborate with business units, vendors, and compliance teams to align delivery with strategic goals.</li></ul> Operational Excellence: <ul><li>Drive continuous improvement across development and delivery processes.</li><li>Maintain technical documentation, design artifacts, and runbooks.</li><li>Participate in capacity planning, disaster recovery, and performance tuning</li></ul> Requirements: <ul><li>Delivery, Project, Stakeholder &amp; Vendor Management experience, &amp; Technical Delivery Leadership</li><li>Experience in actual systems development work, with prior coding, functional specifications and technical specifications and systems development and testing experience</li><li>Strong experience in Cards &amp; Payments domain (Credit Cards, Debit Cards, Transaction Processing, Authorization, Settlement).</li><li>Experience implementing CI/CD pipelines using tools such as Jenkins, Git, Maven, Gradle, and SonarQube.</li></ul>

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: QMS Ownership for Deliverable Software <ul><li>Translate AS9115 Rev A and AS9100:2016 requirements into practical procedures, work instructions, and templates.</li><li>Establish processes covering software planning, development, integration, verification/validation, release, delivery, and post-delivery support.</li><li>Ensure the QMS supports multiple development models (Agile, Waterfall, Incremental) while enforcing required quality controls including reviews, approvals, traceability, and documentation.</li></ul> Software Planning &amp; Requirements Quality <ul><li>Lead the creation and maintenance of Software Quality Plans.</li><li>Establish standards for requirements management ensuring requirements are:</li></ul> <ul><li>Clear</li><li>Unambiguous</li><li>Testable</li><li>Maintain bidirectional traceability from:</li><li>Requirements → Design → Code → Test → Release.</li></ul> Configuration Management &amp; Change Control Define standards for Software Configuration Management (CM) including: <ul><li>Baselines</li><li>Configuration item identification</li><li>Change evaluation and approval</li><li>Configuration status accounting</li><li>Integrate software configuration management with product and system configuration processes.</li><li>Ensure CM covers software, documentation, tools, environments, and build/release artifacts.</li></ul> Supplier &amp; COTS/NDS Management <ul><li>Establish standards for evaluation and acceptance of Commercial Off-The-Shelf (COTS) and Non-Developmental Software (NDS) used in deliverable products.</li><li>Define AS9115 control applicability with both customers and suppliers.</li><li>Support supplier qualification, audits, and incoming verification for software deliverables and services.</li></ul> Verification, Validation &amp; Test Assurance <ul><li>Define verification standards within the QMS including:</li><li>Static analysis</li><li>Peer reviews</li><li>Unit testing</li><li>Integration testing</li><li>System testing</li><li>Regression testing</li><li>Security testing</li><li>Ensure independence of verification activities where required.</li><li>Maintain controlled test environments, data integrity, and objective evidence for compliance audits.</li></ul> Release, Delivery &amp; Post-Delivery Support Develop procedures for: <ul><li>Software release criteria</li><li>Delivery records</li><li>Installation documentation</li><li>Post-delivery issue management</li><li>Patching and configuration updates</li><li>Ensure all processes align with AS9115 standards.</li></ul> Audits, Metrics &amp; Continuous Improvement Lead internal and customer audits related to AS9115/AS9100 compliance. <ul><li>Manage Corrective and Preventive Actions (CAPA).</li><li>Support external and second-party audits with aerospace OEMs.</li><li>Define and track key quality KPIs, including:</li><li>Requirements volatility</li><li>Defect density</li><li>Defect escape rate</li><li>Verification coverage</li><li>Audit findings aging</li><li>Build reproducibility</li><li>Change lead time</li></ul> Requirements: Bachelor’s or Master’s degree in: <ul><li>Software Engineering</li><li>Computer Science</li><li>Systems Engineering or a related discipline.</li><li>Minimum 5 years of experience in software quality or software engineering within aerospace, defense, or other regulated industries.</li><li>Hands-on experience implementing AS9100 quality processes with working knowledge of AS9115 software lifecycle controls.</li></ul> Strong experience in: <ul><li>Requirements management</li><li>Configuration management</li><li>Verification and validation</li><li>Software release governance</li><li>Experience managing COTS/NDS software integration and supplier quality.</li><li>Proven ability to lead audit activities and corrective actions using structured problem-solving tools such as:</li><li>5 Why</li><li>Ishikawa</li><li>8D</li></ul> Preferred Qualifications <ul><li>Experience supporting AS9115 second-party audits with aerospace OEMs.</li><li>Familiarity with DO-178C concepts and coordination with DO-254/ED-80 hardware processes.</li><li>Experience with ALM/PLM and configuration management tools, such as:</li><li>Polarion</li><li>IBM DOORS</li><li>CodeBeamer</li><li>Git / GitLab</li><li>Bitbucket</li><li>Azure DevOps</li><li>Knowledge of CI/CD pipelines, static analysis tools, and unit testing frameworks.</li><li>Exposure to CMMI-DEV processes and experience aligning them with AS9115 quality objectives.</li></ul>

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20 cd Jobs found

Assistant Vice President - Principal Engineer

AVP, Principal Software Engineer (Senior Technical lead)

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Data & ML Architect

Staff Advanced Quality Engineer (Software)

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20 cd Jobs found

Assistant Vice President - Principal Engineer

AVP, Principal Software Engineer (Senior Technical lead)

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Data & ML Architect

Staff Advanced Quality Engineer (Software)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

EMPLOYER

TALENT

COMPANY

Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

JOBS BY INDUSTRY

JOBS BY LOCATIONS

MODEL JOBS

JOBS BY CITY

WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.