Experience: reduced from 7+ to 5–6 years

AWS: now mandatory, including Bedrock, cloud APIs, and core AWS services (was GCP-focused before)

AI Models: added requirement for hands-on experience across all major AI models, integrating/orchestrating them into agentic workflows

Python: called out as mandatory

Coding: made explicit that this is a fully coding-mandatory, hands-on AI Agent development role

Need Jd

Job Title: AI Agent Developer (Python + AWS + LLMs)

Experience: 5–6 Years

Location: [Location]

Employment Type: Full-Time

Job Summary

We are looking for a highly skilled AI Agent Developer with 5–6 years of experience in Python development and hands-on expertise in building AI Agentic applications . This is a 100% hands-on coding role , requiring strong software engineering skills along with experience in integrating and orchestrating multiple AI models into production-grade agentic workflows.

The ideal candidate should have strong experience with AWS (mandatory) , including Amazon Bedrock , cloud APIs, and core AWS services, along with expertise in Python, LLMs, RAG, and modern AI frameworks.

Mandatory Skills

- 5–6 years of hands-on software development experience.
- Strong proficiency in Python (Mandatory).
- Hands-on experience developing AI Agents and Agentic AI applications.
- Experience integrating and orchestrating multiple AI models (OpenAI, Claude, Gemini, Llama, Mistral, etc.) into intelligent workflows.
- Solid understanding of LLMs , Prompt Engineering, RAG, Embeddings, Vector Databases, and AI pipelines.
- Experience with AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen , or similar.
- Strong experience with AWS (Mandatory) including:
- Amazon Bedrock
- AWS Lambda
- API Gateway
- S3
- EC2
- IAM




- CloudWatch
- DynamoDB/RDS
- Cloud APIs and AI service integrations
- Experience developing and consuming REST APIs.
- Strong understanding of software design principles, OOP, and scalable application development.
- Experience with Git, CI/CD, Docker, and production deployment.

Key Responsibilities
- Design, develop, and deploy AI Agent solutions using Python.
- Build intelligent multi-agent workflows leveraging multiple foundation models.
- Integrate AI models from different providers and orchestrate them into business workflows.
- Develop RAG pipelines using vector databases and embeddings.
- Build secure and scalable APIs for AI applications.
- Develop cloud-native AI applications using AWS services and Amazon Bedrock.
- Optimize AI agent performance, latency, and cost.
- Collaborate with cross-functional teams to deliver enterprise AI solutions.
- Write clean, maintainable, and production-ready code.

Preferred Skills
- Experience with MCP (Model Context Protocol).
- Knowledge of Kubernetes and containerized deployments.
- Experience with evaluation frameworks and AI observability.
- Exposure to Graph-based agent architectures.
- Knowledge of MLOps concepts.

Required Technologies
- Python
- AWS (Amazon Bedrock, Lambda, API Gateway, S3, EC2, IAM)
- LangChain / LangGraph / CrewAI / AutoGen
- OpenAI, Claude, Gemini, Llama, Mistral
- RAG, Embeddings, Vector Databases (Pinecone, FAISS, Chroma, Weaviate)
- REST APIs
- Docker
- Git
- CI/CD

Note
- This is a completely hands-on coding role.
- Python development is mandatory.
- AWS experience is mandatory.
- Candidates must have practical experience building AI Agents and integrating multiple AI models into production-grade agentic workflows.

📌 Multi AI Agent (Gurugram)
🏢 SysTechCorp
📍 Gurugram