Mid-level AI Engineer (India)

2 - 4 years

0 Lacs

Posted:16 hours ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

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Job Summary:

Join our team as a Mid-level LLM Engineer and help drive the next generation of GenAI-powered applications. You will architect robust solutions, collaborating closely with fellow engineers, product managers, and designers to turn cutting-edge research into real-world impact. If you thrive in a fast-paced, innovation-driven environment and are passionate about clear communication, this is the opportunity for you.


Responsibilities:


  1. Build GenAI applications such as question-answering systems, content generation tools, and extraction pipelines.
  2. Design, implement, and optimize RAG pipelines end-to-end: ingestion, chunking, embedding, prompt templating, evaluation, and deployment.
  3. Develop robust APIs using Python frameworks (FastAPI preferred).
  4. Work with multiple LLMs (OpenAI, Mistral, Anthropic, etc.) and evaluate model performance for different use cases.
  5. Use LangChain, LangGraph, or LangSmith to orchestrate and monitor GenAI workflows.
  6. Deploy applications on AWS or Azure and implement CI/CD for continuous improvement.
  7. Collaborate with data engineers and product managers to translate technical designs into scalable solutions.
  8. Participate in system design discussions, contributing ideas for performance and maintainability.



Must-have Skills:


  1. Python

    : Strong experience with the language. Able to design clean, modular, production-grade code.
  2. API Development

    : Proven experience building and maintaining APIs (FastAPI/Flask).
  3. GenAI Stack

    : LangChain, LangGraph, LangSmith; multiple LLM APIs (OpenAI, Mistral, etc.).
  4. RAG Lifecycle

    : Data ingestion, prompt templating (Jinja), evaluation/re-ranking, deployment.
  5. Cloud/DevOps

    : Hands-on with AWS or Azure (deployments, monitoring).



Good-to-have Skills:


  1. Understanding of distributed systems and scaling strategies.
  2. Experience with containerization (Docker) and orchestration (Kubernetes).
  3. Familiarity with Guardrails AI or Responsible AI frameworks.
  4. Basic UI integration knowledge (React, optional).



Our interview process is streamlined with a single step: an AI interview. If you perform well, our hiring managers will review your AI interview recording and may extend an offer directly based on that review.

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