AI/ML Engineer

On-siteSeniorAI Engineerposted 2mo ago

✦Role summaryAI-generated

This role demands deep expertise in building and scaling end-to-end GenAI applications, focusing on LLM orchestration, agentic systems, and production-grade deployment with cloud platforms. Candidates should excel in prompt engineering, RAG architectures, and ensuring AI systems meet performance, security, and compliance standards.

About this role

AI/ML Engineer1

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, MS CoPilot)
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