Capgemini
AWS API Engineer / Data Architect
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Who You Will Be Working With
As an AWS API Engineer / Data Architect at Capgemini, you'll design and deliver secure, scalable APIs and microservices that connect systems, data and, increasingly, AI agents. APIs are where modern AI meets the enterprise: they're how an agent retrieves context, calls a tool, or takes an action, so the quality, security and governance of your interfaces directly shapes whether AI-driven systems behave safely and predictably. You'll own solutions from design through build, deployment and production support, making sure services are observable, reliable and cost-effective on AWS.
You'll be part of the Data Platforms team within the Insights and Data Global Practice, which has seen strong, sustained growth across a wide range of sectors. Data Platforms is home to Data Engineers, Platform Engineers, Solution Architects and Business Analysts driving our customers' digital and data transformation on modern cloud platforms. We specialise in the latest frameworks, reference architectures and technologies across AWS, Azure and GCP, and data platforms such as Databricks and Snowflake.
Please Note: Security Clearance: To be appointed to this role, you must be eligible to obtain UK Security Check (SC) clearance. To obtain SC clearance, you must have resided continuously in the United Kingdom for the last 5 years, along with other criteria. Throughout the recruitment process you'll be asked about your security clearance eligibility, including country of residence and nationality. Some posts are restricted to sole UK Nationals for security reasons, so you may be asked about your citizenship.
The Focus of Your Role
You'll take primary responsibility for API and microservices data architecture and system integration on AWS. You'll design RESTful APIs and clean service boundaries, define integration standards, and increasingly design agent-ready interfaces: endpoints that AI agents and LLM-based applications can call safely and reliably. You will participate in data architecture decisions (such as PostgreSQL, document and vector stores) that enable robust, end-to-end, AI-enabled solutions. You'll work with product, delivery, data and cybersecurity colleagues to ensure secure access patterns, strong observability and smooth deployments. Where needed, you'll also contribute to.
What you'll be doing
- Design serverless and microservices APIs on AWS. Build API architectures using Lambda and API Gateway, aligned to product roadmaps, with consistent design patterns, versioning and documentation across the API lifecycle.
- Design agent-ready and tool-calling interfaces. Build APIs that AI agents and LLM applications can invoke, including exposing data and capabilities through patterns such as the Model Context Protocol (MCP), with clear schemas, scoped machine identities and appropriate guardrails so autonomous callers behave safely.
- Support system and data integration. Enable integration across distributed services, including event-driven patterns, and contribute to retrieval and vector data access for RAG and other AI use cases where required.
- Own secure access patterns. Integrate with identity providers and enforce IAM and token-based authentication, designing access control that works for autonomous (non-human) callers as well as users.
- Build in observability and auditability. Implement logging, monitoring, tracing and audit trails, including for non-deterministic AI-driven traffic, with clear human oversight of what agents are permitted to do.
- Modernise pragmatically. Assess and address technical debt and recommend sensible modernisation approaches, and support deployment planning, cutover and post-go-live stabilisation.
- Contribute to data architecture. Help shape document store and data design (PostgreSQL, document and vector stores) in collaboration with data engineering teams.
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What You'll Bring
You'll bring strong, hands-on experience delivering API and integration solutions in complex, often regulated environments, and an interest in how AI agents change what good API design looks like. You don't need to have built agent-facing systems already, but you should be ready to, and able to show the integration and security fundamentals that make them safe.
Essential:
- Strong, hands-on experience designing and building APIs and microservices in production.
- Hands-on experience with AWS serverless technologies (Lambda, API Gateway) and sound security and networking fundamentals (IAM, VPC, and similar).
- Solid understanding of RESTful APIs, integration patterns and distributed systems.
- Proficiency in at least one backend language (e.g. Python) with strong software engineering practice (Git, code review, unit testing, CI/CD) and the ability to troubleshoot production issues.
- Experience across the delivery lifecycle (CI/CD, release planning, cutover, post-go-live stabilisation) and with observability tooling (CloudWatch and/or ELK, Prometheus, Grafana).
- Clear communication of architecture decisions to technical and non-technical stakeholders.
Nice to have:
- Exposure to AI and agentic integration: tool-calling or function-calling APIs, MCP, Amazon Bedrock and Bedrock Agents, Knowledge Bases for Bedrock, or vector search (e.g. OpenSearch, pgvector).
- GraphQL (Apollo).
- Event streaming (e.g. Apache Kafka).
- Progress toward AWS certification (Developer Associate, Solutions Architect Associate or Professional, or Security Specialty).
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Technologies you may work with:
- AWS: Lambda, API Gateway, Aurora/RDS, EC2, Route 53, ECR, STS, VPC, S3, and Amazon Bedrock for AI integration.
- API, integration and security: RESTful APIs, Apollo GraphQL, MCP; IAM, token-based authentication, external identity providers.
- Data and messaging: PostgreSQL, Apache Kafka, document and vector stores.
- Engineering and operations: CI/CD pipelines, ELK stack, Prometheus, Grafana.
Additional Info
Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time. If you are successfully offered this position, you will go through a series of pre-employment checks, including identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service)
What we’ll offer you
You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements. You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.
Why we’re different
At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that’s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.
Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.
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