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3 Days ago

AI Engineer (RAG & FineâTuning Specialist)

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700000 - 2000000 INR - Yearly
Information Technology
Full-Time
Lalitech

Overview

Location: Hybrid/ Remote

Type: Contract / Full‑Time

Experience: 5+ Years

Qualification: Bachelor’s or Master’s in Computer Science or a related technical field

Responsibilities

  • Architect & implement the RAG pipeline: embeddings ingestion, vector search (MongoDB Atlas or similar), and context-aware chat generation.
  • Design and build Python‑based services (FastAPI) for generating and updating embeddings.
  • Host and apply LoRA/QLoRA adapters for per‑user fine‑tuning.
  • Automate data pipelines to ingest daily user logs, chunk text, and upsert embeddings into the vector store.
  • Develop Node.js/Express APIs that orchestrate embedding, retrieval, and LLM inference for real‑time chat.
  • Manage vector index lifecycle and similarity metrics (cosine/dot‑product).
  • Deploy and optimize on AWS (Lambda, EC2, SageMaker), containerization (Docker), and monitoring for latency, costs, and error rates.
  • Collaborate with frontend engineers to define API contracts and demo endpoints.
  • Document architecture diagrams, API specifications, and runbooks for future team onboarding.

Required Skills

  • Strong Python expertise (FastAPI, async programming).
  • Proficiency with Node.js and Express for API development.
  • Experience with vector databases (MongoDB Atlas Vector Search, Pinecone, Weaviate) and similarity search.
  • Familiarity with OpenAI’s APIs (embeddings, chat completions).
  • Hands‑on with parameters‑efficient fine‑tuning (LoRA, QLoRA, PEFT/Hugging Face).
  • Knowledge of LLM hosting best practices on AWS (EC2, Lambda, SageMaker).

Containerization Skills (Docker)

  • Good understanding of RAG architectures, prompt design, and memory management.
  • Strong Git workflow and collaborative development practices (GitHub, CI/CD).

Nice‑to‑Have

  • Experience with Llama family models or other open‑source LLMs.
  • Familiarity with MongoDB Atlas free tier and cluster management.
  • Background in data engineering for streaming or batch processing.
  • Knowledge of monitoring & observability tools (Prometheus, Grafana, CloudWatch).
  • Frontend skills in React to prototype demo UIs.

Skills:- Artificial Intelligence (AI), Generative AI, Python, NodeJS (Node.js), Vector database, Amazon Web Services (AWS), Docker, Retrieval Augmented Generation (RAG) and CI/CD
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