AI / ML Engineer

Required Qualifications

7+ years in software engineering or applied ML building real-world AI / ML systems; strong Python proficiency and backend development expertise.

Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state / memory management, and graph-based orchestration.

Proficiency in ML / NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration / fine-tuning (OpenAI, LLaMA, Cohere, etc.)

Strong coding in Python and experience with frameworks / tools such as FastAPI, PyTorch / TensorFlow, MLflow; solid understanding of software engineering fundamentals and secure development.

Experience with AI agent frameworks and MCP; familiarity with agent observability (LangSmith / LangFuse) and agentic RAG patterns

Track record of delivering scalable, production AI systems and collaborating across teams.

Experience with agent frameworks (AutoGen, CrewAI), tool-use ecosystems, and advanced planning / reasoning strategies

Knowledge of cloud platforms (AWS), MLOps, and data pipelines; React.js familiarity is a plus.

Exposure to enterprise environments and secure, compliant deployments

Key Skills

• Programming : Python; backend APIs (FastAPI)
• AI / ML : ML / NLP, generative AI, embeddings, model evaluation
• Frameworks : LangChain, LangGraph; plus LlamaIndex, PyTorch, TensorFlow, MLflow
• Architectures : RAG, Transformers, OCR
• Agents : Design and orchestration, memory / state management, tool integration; MCP and agent-to-agent protocols

Observability : LangSmith / LangFuse for agent monitoring