Assistant Vice President - Principal Engineer

AVP, Solution Architect

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

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

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>Influence many agile development teams through all phases of the Agile development life cycle through SAFe</li><li>Implement new technologies and assist developers as they migrate to new technologies</li><li>Architect applications across the full stack, experience in PCF, AWS, Cloud Native</li><li>Application Architecture, Microservices ecosystem, Spring Batch Apps using Spring Cloud Data Flow, J2EE, Spring Java, and RESTful APIs are a must.</li><li>Design data models to support complex business processes</li><li>Drive a CI/CD strategy using our Jenkins, Bitbucket, and uDeploy stack.</li><li>Influence and collaborate with software developers, UX designers, product managers, application architects, and customer application experts to create amazing apps.</li><li>Mentor and influence all levels of the team: in this role, you will have the opportunity to influence up and down the chain of command</li><li>Ensure compliance with architecture, security and technology standards set by company Financial</li><li>Assist in crafting and maintaining the future state technology architectural strategy, along with our application of modernization and migration roadmap.</li><li>Participate in Agile scrums consisting of cross-functional teams</li><li>Participate and Contribute towards Engineering Community of Practices (CoPs)</li><li>Lead Agile sprints as the technical expert, including sprint planning, daily standups, backlog grooming sessions, and sprint reviews</li><li>Ensure application code quality through development, test, and QA</li><li>Participate in addressing root cause analyses, incident reports and provide direction in problem resolution</li><li>Analyze production defects, troubleshoot systems, identify root cause, and implement fixes</li><li>Passionate about the latest technologies, open-source projects and languages</li><li>Provide 24x7 on-call support periodically throughout the year</li><li>Identify ways to increase efficiency and improve system performance</li><li>Work with third party vendors to develop software and/or integrate their software into the companys products</li></ul> Requirements: <ul><li>Bachelors degree in computer science or related degree with modern application</li><li>development experience, around 7 years of experience in Technology, 5+ years in</li><li>API development using Java and 2 years in Technical Lead driving product solutions in</li><li>Enterprise Communications</li><li>Strong Technical Expertise in Java, Spring Projects – Spring Boot, Spring Framework, Spring Cloud, Spring Batch, Spring Cloud Data Flow, S3 Bucket, Git, Maven, Gradle and REST</li><li>Prior experience working with US Payment networks (ACH, Wire, or related payment processing systems) is essential</li><li>Strong Experience in developing microservices with 12-factor app methodology</li><li>Strong Experience with Scaled Agile framework and familiarity with tools like JIRA Align</li><li>Strong Experience with Agile application development and familiarity with tools like JIRA</li><li>Strong Experience with continuous integration environments and using tools like Jenkins</li><li>Strong Experience writing unit and integration tests and familiarity with frameworks like Junit, Mockito, Spring Test.</li><li>Strong Experience with Caching Systems – Redis/Gemfire.</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>

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>

Role Description: <ul><li>Working closely with the Data Scientists and be responsible for implementing large language models (LLMs) based applications, working with proprietary and open-source Models as well as popular frameworks such as Lang Chain to ensure seamless integration and deployment.</li></ul> Responsibilities: <ul><li>Building standalone applications that interact with LLM models.</li><li>Building RAG-based applications.</li><li>Understanding of Vector DBs like Solr for LLM based applications</li><li>Integrate models with existing systems and APIs.</li><li>Implement production quality ETL jobs</li><li>Preprocess and manage data for training and deployment.</li><li>Collaborate with cross-functional teams to define, design, and ship new features.</li><li>Write clean, maintainable, and efficient code.</li><li>Document development processes, code, and APIs.</li></ul> Requirements: <ul><li>Degree in Computer Science, Data Science, or related field.• Proven experience in building customer facing ML based APIs</li><li>Mexico City–based (or nearby), available to work onsite 2 days per week at Glorietadel Ahuehuete, Reforma.</li><li>Experience in developing applications that are scalable to handle TBs of data</li><li>Strong knowledge of API integration (RESTful, GraphQL).</li><li>Experience with data preprocessing, SQL, and NoSQL databases as well as vector stores (e.g., Postgres, MySQL, Solr, Elasticsearch/OpenSearch, etc.).</li><li>Familiarity with deployment tools (Docker, Kubernetes).</li><li>Experience with DevOps tools like Jenkins, Terraform, Cloud Formation templates is highly preferred.</li><li>Excellent problem-solving and communication skills.</li><li>Experience with Spark/Hadoop, EMR or any other Big Data technology would be a plus</li><li>Experience working on agents is considered a good-to-have</li><li>Familiarity with agents, even through courses Work in a way that works for you We promote a healthy work/life balance across the organization..</li></ul> Other Information: These are some of the benefits we are delighted to offer: <ul><li>Private Medical/Dental Plan.</li><li>Savings Fund.</li><li>Life Insurance.</li><li>Meal/Grocery Voucher.</li><li>We offer an appealing working prospect for our people.</li><li>With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.</li><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working for you.</li><li>We know that your well-being and happiness are key to a long and successful career.</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Develop detailed test plans based on project requirements and specifications.&nbsp;</li><li>Provide feedback on quality standards, usability, and areas for improvement.</li><li>Automates test scenarios and expected outcomes.&nbsp;</li><li>Conduct regression, integration, user acceptance, and performance testing.</li><li>Conducts comprehensive testing and risk-based assessments of the testing objects.&nbsp;</li><li>He/She uses source documentation as input and contributes to the planning and implementation of testing activities.&nbsp;</li><li>Leads testing components of large and complex projects, assigns tasks, provides direction to resources, and reports progress to project stakeholders.&nbsp;</li><li>He/She creates and selects tools and methodologies for review and approval by management.</li></ul> ﻿Requirements: <ul><li>Bachelors Degree or International equivalent&nbsp;</li><li>Bachelors Degree or International equivalent in Computer Science, Information Systems, Mathematics, Statistics or related field - Preferred&nbsp;</li><li>comprehensive knowledge of technical skills, principles, practices, and procedures of testing methodologies and working knowledge in planning, designing, and conducting QA reviews and inspections.&nbsp;</li><li>He/She provides expertise for key business functions and supporting technologies.&nbsp;</li><li>Provides mentorship and expertise in technologies and processes for Information Services Management (ISM) and Quality Assurance (QA).&nbsp;</li><li>He/She maintains an awareness of emerging technologies to ensure a competitive advantage.</li><li>Experience with both web and client/server based testing</li><li>Minimum 8 Years of Relevant Experience in IT Test Automation.</li><li>Should have strong Mainframe testing [CICS, JCL, DB2, Cobol]</li><li>Must be able to test and debug batch jobs (JCL).</li><li>Must be able to perform backend testing by executing SQL queries.</li><li>Expertise in APIs &amp; Web Services testing</li><li>Hands-on experience in Selenium, TestNG and Cucumber frameworks</li><li>Good in test execution reporting skills</li><li>Expertise in Test Cases Design and Test Data management</li><li>Expertise in tools like PostMan, SOAP UI, WinSCP, Oracle, Jenkins, GitHub and AppDynamics.</li><li>Should be well versed with Agile testing and Continuous Testing</li><li>Experience with Test Management tools</li><li>Knowledge on AZURE DEVOPS&nbsp;</li><li>Understanding of SAFe Agile methodologies</li><li>Should be solution-oriented and have problem solving aptitude</li><li>Should have excellent communication and presentation skills</li><li>Knowledge on Logistics domain will be an advantage</li><li>Good to have Performance Testing experience.</li><li>Knowledge on JMeter / Performance center will be an advantage.</li><li>Any certifications in test automation</li></ul>

Responsibilities: <ul><li>Demonstrated ability to drive cultural change and advocate for cloud transformation Key Responsibilities Cloud Strategy &amp; Leadership&nbsp;</li><li>Develop and implement a comprehensive AWS cloud strategy, ensuring alignment with business and technology goals.&nbsp;</li><li>Provide technical leadership and advocacy, championing cloud-native best practices and innovation.&nbsp;</li><li>Lead and drive architectural decisions, ensuring scalability, security, and operational efficiency.</li><li>Cloud Architecture &amp; Design&nbsp;</li><li>Architect secure, scalable, and highly available AWS cloud environments.&nbsp;</li><li>Develop and maintain enterprise-wide cloud blueprints, patterns, and frameworks to drive consistency.&nbsp;</li><li>Research and integrate emerging cloud technologies to foster continuous innovation. Infrastructure as Code &amp; Automation&nbsp;</li><li>Lead adoption and implementation of Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, and Helm.&nbsp;</li><li>Design and optimize CI/CD pipelines to streamline cloud deployments and operations.&nbsp;</li><li>Implement self-healing and automated failover mechanisms to enhance resilience and reliability.</li><li>Kubernetes &amp; Cloud-Native Technologies&nbsp;</li><li>Manage and optimize Kubernetes clusters (EKS, Helm, IAM) for scalability and security.&nbsp;</li><li>Define and enforce best practices for containerized applications and orchestration.&nbsp;</li><li>Improve Kubernetes networking, ingress, and observability solutions to enhance performance. Security &amp; Compliance&nbsp;</li><li>Establish and enforce security best practices for AWS environments, including IAM, WAF, Secret Manager, and encryption.&nbsp;</li><li>Implement zero-trust security models and secure multi-account AWS environments.&nbsp;</li><li>Conduct security audits, incident response, and ensure compliance with industry standards. Monitoring, Logging &amp; Reliability Engineering.</li><li>Deploy and manage monitoring tools (DataDog, Splunk, CloudWatch, Coralogix) to ensure visibility and observability.&nbsp;</li><li>Implement SRE principles to enhance system uptime, reliability, and efficiency.&nbsp;</li><li>Conduct post-mortem analysis and drive continuous improvements in cloud performance. Collaboration &amp; Thought Leadership&nbsp;</li><li>Work closely with software developers, system engineers, and security teams to design and implement cloud solutions.&nbsp;</li><li>Provide mentorship, training, and technical leadership to engineering teams.&nbsp;</li></ul> Requirements: <ul><li>10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li>Deep understanding of AWS services, including EC2, EKS, RDS, S3, Lambda, VPC, IAM, Transit Gateway, and CloudFormation.&nbsp;</li><li>Expertise in Kubernetes (EKS, Helm, Daemon Sets, StatefulSets, Karpenter, external-dns, aws-cni).&nbsp;</li><li>Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).&nbsp;</li><li>Hands-on experience managing CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).&nbsp;</li><li>Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).&nbsp;</li><li>Strong networking and security knowledge (DNS, VPC, NAT, Security Groups, IAM).&nbsp;</li><li>Experience designing and developing scalable, production-grade software tools and automation scripts using Python. Preferred Certifications&nbsp;</li><li>AWS Certified Solutions Architect – Professional (or equivalent).&nbsp;</li><li>Additional certifications in Kubernetes (CKA), AWS Security, or DevOps are a plus. Leadership &amp; Soft Skills&nbsp;</li><li>Proven experience leading cloud architecture and strategy initiatives.&nbsp;</li><li>Ability to mentor and guide technical teams in a fast-paced, agile environment.&nbsp;</li><li>Strong problem-solving and troubleshooting skills in complex cloud environments.</li><li>Excellent communication skills with the ability to translate technical concepts for engineering, business, and executive stakeholders.&nbsp;</li></ul>

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Assistant Vice President - Principal Engineer

AVP, Solution Architect

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

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

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Assistant Vice President - Principal Engineer

AVP, Solution Architect

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

Lead Quality Automation Engineer

Forward Deployed AI Scientist

Technical Development Lead, Cards (Microservices, JAVA development)

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

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