Python Developer – GenAI & Agentic AI

Hiring : Python Developer – GenAI & Agentic AI | 5–7 Years | Bangalore / Remote | Immediate Joiners Location : Bangalore / Remote

Experience : 5–7 Years

Budget : 1.6 – 1.7 LPM

Notice Period : Immediate (Bench resources only)

Mode : Remote / Hybrid

⚠️ Note : Candidates must have ESI / Medical Insurance, EPFO Registration, PT Registration, Labour Welfare Fund Registration, Shop Act Registration, and GST Registration .

Only profiles with these compliance documents will be considered.

✨ About the Role We are looking for an experienced Python Developer specialized in Generative AI (GenAI) and Agentic AI . The ideal candidate will be proficient in LLM-based application development, RAG pipelines, AI agents, LangChain / LangGraph, and cloud AI services. You will design and deploy scalable AI-driven solutions used across enterprise environments.

Key Responsibilities Develop GenAI Applications : Build and optimize AI solutions using Python, LangChain, LangGraph, MCP, and AgentOps.

LLM Integration : Work with Azure AI, AWS Bedrock, OpenAI, Anthropic, and other LLM providers for text, multimodal, and agent workflows.

RAG Architecture : Implement Retrieval-Augmented Generation pipelines with vector DBs (Pinecone, Chroma, Weaviate, FAISS).

Fine-tuning & MLOps : Fine-tune LLMs for domain tasks; build CI / CD pipelines for ML models using MLOps tools and best practices.

Agentic AI Systems : Design multi-agent workflows with orchestration, memory, planning, and error-handling capabilities.

Cloud Deployment : Deploy models / applications on AWS (Lambda, EC2, S3, Bedrock, SageMaker) and Azure AI.

Performance & Cost Optimization : Optimize model response time, scalability, and cloud compute cost.

Cross-functional Collaboration : Work closely with Data Science, DevOps, and Product teams to deliver robust AI solutions.

Required Skills & Qualifications Strong proficiency in Python and backend development.

Hands-on experience with LangChain, LangGraph, MCP, AgentOps .

Strong understanding of RAG pipelines and vector DBs (Pinecone, Chroma, Weaviate, FAISS).

Experience in LLM fine-tuning and prompt engineering.

Solid knowledge of MLOps (CI / CD, monitoring, model deployment).

Experience using cloud AI platforms : AWS Bedrock, Azure AI, SageMaker, GCP Vertex AI (preferred).

Understanding of Agentic AI (multi-agent orchestration, planning, memory).

Familiarity with Docker, Kubernetes, Terraform, GitOps .

Strong analytical, debugging, and problem-solving skills.

⭐ Preferred Qualifications Experience with multimodal models (text, image, audio).

Exposure to enterprise AI compliance and security frameworks .

Knowledge of ISO / IEC AI governance standards .

Contributions to open-source AI / ML projects .

How to Apply If your profile matches and you meet the compliance requirements, please share your resume at [Add Email / Apply Link] .

Immediate joiners are highly preferred.