FullStack AWS AI Engineer

Role Name:    FullStack AWS AI Engineer
Location:    Malvern / Hybrid
Start date:    2026-10-13
Background check MANDATORY
Due to additional onboarding requirements, a meet and greet is required for all new hires.
Candidates must be willing to go to the closest Capgemini, Client, or onsite  location as indicated by project team to meet with a Capgemini team member prior starting their assignment. If the candidate is not local, travel covered by Capgemini.  If travel is involved and after selection the candidate declines the offer, costs will be paid by vendor and not Capgemini.
JOB DESCRIPTION:    
We are seeking a Full‑Stack AWS AI Engineer (5+ Years) to design, build, and scale cloud‑native, AI‑powered applications on AWS. This role blends front‑end and back‑end engineering, machine learning / GenAI integration, and AWS cloud architecture, with strong emphasis on security, scalability, and production readiness. The engineer will work closely with product, data science, and platform teams to operationalize AI capabilities into real‑world applications.

Key Responsibilities
Agentic & GenAI
Design, develop, and deploy Agentic and Generative AI solutions using AWS AI services (Amazon SageMaker, Bedrock, Rekognition, Textract, Transcribe, Translate).
Integrate foundation models / LLMs into applications using Bedrock or custom model endpoints.
Build AI pipelines for inference, prompt orchestration, fine‑tuning, and evaluation.
Implement responsible AI practices including auditability, explainability, bias mitigation, and model governance.
AWS Cloud Architecture & DevOps
Architect and deploy cloud‑native solutions using AWS core services:
EC2, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS, Aurora, Step Functions.
Implement Infrastructure as Code (IaC) using CloudFormation, CDK, or Terraform.
Design CI/CD pipelines leveraging GitHub Actions, AWS CodePipeline, or similar tools.
Optimize performance, availability, and cost using AWS Well‑Architected Framework principles.
Security, Compliance & Operations
Enforce AWS security best practices (IAM, KMS, VPC design, encryption at rest/in transit).
Implement monitoring, logging, and alerting using CloudWatch, X‑Ray, and OpenSearch.
Support compliance requirements (SOC2, ISO, financial services governance where applicable).
Participate in production support, troubleshooting, and performance tuning.
Required Qualifications

Technical Skills
Strong experience in full‑stack development (front‑end + back‑end).
Hands‑on expertise with AWS services and cloud‑native architectures.
Practical experience building or integrating Agentic or Generative AI solutions.
Proficiency in at least one backend language (Python preferred).
Experience with REST APIs, microservices, and asynchronous processing.
Familiarity with containerization (Docker) and orchestration (ECS/EKS).
Engineering & Delivery
Experience building production‑grade systems, not just prototypes.
Strong understanding of software design patterns, scalability, and resilience.
Ability to translate business problems into technical AI solutions.
Experience working in Agile / DevOps teams.