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Assistant Manager

exl Service.com (India) Private Limited
Bengaluru, IND
Full-time
Manager · 3+ years experience
Hybrid
Discovered 3 weeks ago
fastapikafkalangchainpythonsql

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Qualifications

  • Minimum Qualifications
  • Bachelor's degree in Computer Science, Data Science, or related field
  • 3+ years of total professional experience, including:
  • 3+ years of hands-on Software Engineering experience in Python, FastAPI and relevant tech stack
  • 2+ years working specifically with GenAI and LLMs (GPT, Claude, LLaMA, etc.)
  • Track record of shipping production ML/AI products, with strong prompt-engineering skills, systems-level thinking, and the ability to diagnose and resolve production failures
  • Strong software engineering background with expertise in OOP and SOLID principles
  • Proficiency in Python 3.11+ (async/await, type hints, modern Python patterns, strict type checking)
  • Experience with agentic frameworks (LangChain, LangGraph, AutoGen, or similar)
  • Proven track record building production REST/WebSocket APIs and microservices
  • Experience with message streaming platforms (Kafka, Pulsar, or similar)
  • Strong knowledge of databases: SQL, NoSQL, and vector databases
  • Working knowledge of RAG pipelines (embeddings, chunking, retrieval) and LLM observability/evaluation tools (LangSmith, Langfuse, or similar)

Responsibilities

  • Key Responsibilities
  • 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 frameworks

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