AI/ML Engineer2
Key Responsibilities
Build and deploy LLM-based GenAI applications end-to-end
Work with multiple LLMs (OpenAI/Azure OpenAI, Gemini, Claude, LLaMA, Mistral)
Design and implement agentic and multi-agent systems using MCP and A2A
Develop RAG pipelines and document intelligence solutions
Use modern GenAI frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Google ADK)
Build AI backend services using FastAPI and Flask
Develop and integrate chat UIs, copilots, and dashboards with AI APIs
Productionize, deploy, and monitor AI systems on cloud platforms
Ensure performance, security, scalability, and Responsible AI compliance
Required Skills
Strong Python programming with FastAPI and Flask
Solid understanding of ML, Deep Learning, NLP, and GenAI concepts
Hands-on experience with LLMs, embeddings, and prompt engineering
Experience designing agentic systems with MCP / A2A
Expertise in RAG architectures and vector databases (FAISS, Pinecone, Weaviate, Chroma, Milvus)
Working knowledge of front-end technologies: HTML, CSS, JavaScript, Stremlit; React preferred
API design and integration (REST / WebSockets)
Strong deployment & MLOps experience: Azure / AWS / GCP, Docker, Kubernetes, CI/CD, MLflow / Azure ML / SageMaker / Vertex AI
Good to Have
Fine-tuning open-source LLMs (LoRA, PEFT, Hugging Face)
Experience with autonomous agents and async workflows
Exposure to RPA + Agentic AI integration
Knowledge of AI governance, monitoring, and security
