AWS Developer – Generative AI / AWS Bedrock

Location: Lansing, MI – Onsite
Relocation: Candidates open to relocation are welcome
Duration: 6+ Months Contract
Rate: $55/hr C2C MAX
Employment Type: Contract
Visa: Any visa except H1B & CPT
Interview: As per client process

Candidate Submission Requirements

Interested candidates, please share the following details at abhishek@teknohire.com:

Updated Resume:
LinkedIn URL:
Relocation:
Current Location (As Per DL):
Work Authorization:

2 Manager/Lead References

Reference 1
Name –
Title –
Email –
Phone –
LinkedIn URL –

Reference 2
Name –
Title –
Email –
Phone –
LinkedIn URL –

Please submit only candidates who are comfortable relocating to Lansing, MI and working onsite.

Job Overview

Client GPS is seeking an experienced AWS Developer – Generative AI / AWS Bedrock to support a State of Michigan project.

The role will focus heavily on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, AWS Bedrock, and cloud-native application development.

The ideal candidate will have strong hands-on experience with Python and AWS development and a proven ability to build AI-powered applications and integrate Generative AI capabilities into enterprise environments.

This is not a traditional AWS infrastructure role. Candidates should have hands-on experience developing and implementing GenAI/LLM solutions in AWS environments.

Must-Have Technical Skills

Strong hands-on Python development experience.
Strong AWS cloud development experience.
Hands-on Generative AI / LLM experience.
Experience designing and implementing RAG (Retrieval-Augmented Generation) solutions.
Experience with Agentic AI frameworks and AI agent development.
Strong prompt engineering experience.
Experience working with structured LLM outputs.
Experience with LLM orchestration.
Hands-on AWS Bedrock experience.
Strong FastAPI and REST API development experience.
Experience with AWS Lambda.
Experience with AWS API Gateway.
Experience with AWS CloudFormation.
Experience with AWS Fargate.
Experience with Amazon OpenSearch.
Experience building cloud-native/serverless applications.
Hands-on Amazon Connect experience, including contact flows and AI integrations.

Key Responsibilities

Build and deploy AI-powered applications using Generative AI, LLMs, and Agentic AI frameworks.
Design and implement scalable RAG solutions.
Perform prompt engineering and develop structured LLM outputs.
Implement LLM orchestration using Python and modern AI frameworks.
Evaluate LLM performance and continuously improve AI solutions.
Develop scalable REST APIs and FastAPI services.
Build and deploy cloud-native applications within AWS.
Integrate AWS Bedrock into enterprise applications.
Develop AI-powered knowledge assistants, Q&A chatbots, and intelligent business solutions.
Configure and enhance Amazon Connect contact flows.
Integrate AI capabilities into Amazon Connect and customer engagement solutions.
Develop scalable serverless applications using AWS Lambda and API Gateway.
Utilize CloudFormation for infrastructure automation and deployment.
Build containerized solutions using AWS Fargate.
Implement search and retrieval capabilities using Amazon OpenSearch.
Collaborate with architects, developers, technical teams, and business stakeholders to translate requirements into scalable AI solutions.
Follow enterprise standards for security, scalability, reliability, and maintainability.
Troubleshoot and optimize application performance and AI solution quality.

Ideal Candidate

The ideal candidate will have a combination of:

Python
AWS
Generative AI / LLM
AWS Bedrock
RAG
Agentic AI
FastAPI
Amazon Connect

Candidates with only traditional AWS infrastructure/DevOps experience without hands-on Generative AI/LLM development experience will not be a strong fit.

Preferred Experience

LangChain, LangGraph, or similar AI orchestration frameworks.
Experience developing AI agents and agentic workflows.
Experience with enterprise knowledge assistants and intelligent Q&A applications.
Experience with vector databases and semantic search.
Experience with RESTful API architecture.
Experience with serverless AWS architectures.
Experience working with state government or large enterprise environments.
Experience integrating Generative AI into existing business applications.