Key Responsibilities

Leadership & Strategy

• Lead architectural design and implementation of multi-agent AI systems

• Drive technical strategy for GenAI initiatives and recommend best practices

• Mentor and provide technical guidance to junior and mid-level engineers

• Collaborate with stakeholders to define requirements and deliver solutions

• Own end-to-end delivery of complex, production-scale AI systems

Technical Execution

• Build and maintain high-performance REST/WebSocket APIs using FastAPI (Pydantic v2)

• Implement and optimize agentic AI systems using frameworks like LangGraph, Deep Agents, AutoGen, and LangChain

• Architect real-time, event-driven microservices using messaging queues like Apache Kafka

• Design clean, testable, maintainable services using SOLID principles, Python async, and type hints

• Integrate and optimize SQL, NoSQL, and vector databases (Postgres, MongoDB, ChromaDB, Pinecone)

• Run LangGraph/Deep Agents workflows in production with checkpointing, persistence, and human-in-the-loop controls,



backed by LLM observability and evaluation tooling (e.g., LangSmith, Langfuse)

• Apply LLM safety guardrails (prompt-injection mitigation, PII handling, content moderation) in line with Banking, Insurance, and Healthcare compliance requirements

• Stay current with emerging trends in GenAI, deep learning, and AI orchestration framework

Skills and Competencies

• Proven ability to architect and deliver end-to-end GenAI solutions and multi-agent systems

• Robust software engineering discipline: testing (unit, integration, performance), code review, documentation

• Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders

• Strategic thinking and problem-solving with a focus on scalability and maintainability

•
Leadership capability: mentoring, technical guidance, and cross-functional collaboration

Responsibilities
Key Responsibilities

Leadership & Strategy

• Lead architectural

📌 Data Scientist (Noida)
🏢 EXL
📍 Noida