Software Engineer – Ag & Trade

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

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Scientist

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

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>

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</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: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.&nbsp;</li><li>Typically reflects 4 years or more with 3+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 2 years of building production software or data platforms.&nbsp;</li><li>Typically reflects 3 years or more with 2+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</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: <ul><li>Design, develop, and maintain web applications using Java, Spring Boot, React, Redux, and PostgreSQL</li><li>Implement and manage APIs and microservices architecture</li><li>Ensure the performance, quality, and responsiveness of applications</li><li>Identify and correct bottlenecks and fix bugs</li><li>Partner with business stakeholders and operations team to identify and manage KPIs</li><li>Evaluate the performance of processes, services, and outcomes and drive performance improvement</li><li>Independently solve complex issues, lead a team of junior and mid-level developers</li><li>Other duties as assigned</li></ul> Requirements: <ul><li>Bachelor’s degree in computer science, Information Technology, or related field. Minimum of 12-15 years offull stack development related work experience</li><li>Strong oral and written communication skills</li><li>Expert in Java, Spring Boot, React, Redux, and PostgreSQL</li><li>Strong analytical skills with the ability to collect, organize, and analyze data</li><li>Attention to detail and accuracy is critical</li><li>Working knowledge of cloud platforms (e.g., AWS, Azure)</li><li>Adept at presenting findings in MS PowerPoint and MS Word</li></ul>

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22 aws Jobs found

Software Engineer – Ag & Trade

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

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Scientist

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

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22 aws Jobs found

Software Engineer – Ag & Trade

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

VP, Engineering Manager

Lead Quality Automation Engineer

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Scientist

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

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