AWS Generative AI Engineer

Capgemini•Columbia, SC

2d•Hybrid

About The Position

We are seeking a highly skilled AWS Generative AI Engineer with strong experience in designing, developing, and deploying Generative AI solutions on AWS. The ideal candidate should possess hands-on expertise with Amazon Bedrock, Anthropic Claude models, Large Language Models (LLMs), prompt engineering, retrieval augmented generation (RAG), and scalable cloud-native architectures. The role involves collaborating with business and technology teams to build AI-powered applications that drive innovation and business value.

Requirements

Strong experience with AWS Cloud Services.
Hands-on experience with Amazon Bedrock, AWS Lambda, API Gateway, Amazon S3, Amazon DynamoDB, Amazon OpenSearch, ECS/EKS, CloudWatch, IAM.
Strong experience with Amazon Bedrock and Anthropic Claude models.
Solid understanding of Large Language Models (LLMs), Prompt Engineering, RAG Architecture, Vector Databases, AI Agents and Agentic Workflows, Finetuning and Model Evaluation, Responsible AI and AI Governance.
Proficiency in Python.
Experience with LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, SDK integrations.
Experience integrating structured and unstructured data sources.
Knowledge of embeddings, semantic search, knowledge bases, and document ingestion pipelines.
5-10 years of overall software/cloud development experience.
2-4 years of hands-on experience in Generative AI and LLM-based solution development.
Proven experience delivering enterprise-scale AI solutions on AWS.
Solution Design & Architecture.
Generative AI & LLM Expertise.
Cloud Native Development.
Problem Solving & Analytical Thinking.
Stakeholder Management.
Innovation Mindset.
Agile Delivery.
Communication and Collaboration Skills.

Nice To Haves

Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field.
AWS certifications such as AWS Certified Machine Learning Engineer, AWS AI Practitioner.
Experience with MLOps, CI/CD, and infrastructure as code tools (Terraform, CloudFormation).
Familiarity with other LLM providers such as OpenAI, Meta Llama, Mistral, or Cohere.

Responsibilities

Design, develop, and deploy Generative AI solutions leveraging Amazon Bedrock, Anthropic Claude, and other foundation models.
Build and optimize RAG (Retrieval Augmented Generation) architectures using vector databases and enterprise knowledge sources.
Develop AI-powered applications such as chatbots, virtual assistants, document processing, content generation, and intelligent search solutions.
Create and optimize prompts, workflows, and model configurations to improve response quality, accuracy, and performance.
Integrate Bedrock foundation models with enterprise applications, APIs, and AWS services.
Implement scalable and secure cloud-native solutions using AWS services such as Lambda, API Gateway, ECS, EKS, S3, DynamoDB, and OpenSearch.
Finetune model outputs through prompt engineering, guardrails, and evaluation frameworks.
Collaborate with data engineers, architects, product owners, and business stakeholders to identify GenAI use cases and deliver solutions.
Monitor model performance, costs, latency, and security compliance.
Ensure adherence to responsible AI practices, governance, and security standards.
Stay updated with emerging trends in Generative AI, LLMs, and AWS AI/ML services.

Benefits

Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits like adoption assistance, surrogacy, and cryopreservation
Social well-being benefits like subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief