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# Gen AI developer

- **Company:** Capgemini
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $86,549.0 - $135,221.0
- **Contract:** Temporary contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Code Optimization, Computer Programming, Python (Programming Language), Machine Learning, Network Control, Software Engineering, Pinecone, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Vector Embeddings, Generative AI, Agentic-AI, Pgvector, AI Platforms, Kubernetes, FAISS, Front End Software Development, Api Design, Restful APIs, GPT, Microservices
- **Published:** October 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b04f2ce39a0b3fdb

## About the Role

LLM Frameworks
api development
Model Optimization
Vector databases
python programming
Scalability & Performance

We are seeking highly skilled Agentic AI Senior Developers to design, build, and deploy intelligent autonomous systems that leverage large language models (LLMs), tools, and orchestration frameworks. The ideal candidate will have strong experience in AI/ML engineering and hands-on expertise in building multi-step AI agents that can reason, plan, and execute tasks., * 10+ years of hands-on development experience in software engineering / AI development

 * Strong programming skills in Python (mandatory)
 * Experience with LLM frameworks: LangChain, LangGraph is mandatory.
 * Knowledge of vector databases (FAISS, Pinecone, PgVector, etc.)
 * Must have development experience with REST APIs and microservices architecture
 * Must have development experience with AWS / Anthropic AI services
 * Good understanding of prompt engineering, agent tools, agent skills, agent workflows, schematic search, vector embeddings and mcp tools concepts
 * AI and Agents Evals implementation
 * AI and Agents Observability and Control plane integration

Good to Have:

 * Experience with multi-agent orchestration
 * Knowledge of GenAI governance and responsible AI
 * Frontend exposure (React, chat interfaces)
 * Model evaluation, Fine tuning (optional).

## Description

* Design and develop agentic AI systems using LLMs (AWS Bedrock, Anthropic API, etc.)
 * Build multi-agent workflows with planning, memory, and tool usage capabilities
 * Integrate APIs, enterprise systems, and knowledge sources into agent workflows
 * Develop prompt engineering strategies and optimize model performance
 * Implement RAG (Retrieval Augmented Generation) pipelines
 * Ensure scalability, performance, and security of AI systems
 * Collaborate with business teams to translate use cases into AI solutions
 * Monitor agent behavior and continuously improve accuracy and reliability