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LLM Engineer_4+years

LLM Engineer_4+years

ConfidentialPune, India
9 days ago
Job description

Primary Title : Senior LLM Engineer (4+ years) — Hybrid, India

About The Opportunity

A technology consulting firm operating at the intersection of Enterprise AI, Generative AI and Cloud Engineering seeks an experienced LLM-focused engineer. You will build and productionize LLM-powered products and integrations for enterprise customers across knowledge management, search, automation, and conversational AI use-cases. This is a hybrid role based in India for candidates with strong hands-on LLM engineering experience.

Role & Responsibilities

  • Own design and implementation of end-to-end LLM solutions : data ingestion → retrieval (RAG) → fine-tuning → inference and monitoring for production workloads.
  • Develop robust Python microservices to serve LLM inference, retrieval, and agentic workflows using LangChain / LangGraph or equivalent toolkits.
  • Implement and optimise vector search pipelines (FAISS / Pinecone / Milvus), embedding generation, chunking strategies, and relevance tuning for sub-second retrieval.
  • Perform parameter-efficient fine-tuning (LoRA / adapters) and evaluation workflows; manage model versioning and automated validation for quality and safety.
  • Containerise and deploy models and services with Docker and Kubernetes; integrate with cloud infra (AWS / Azure / GCP) and CI / CD for repeatable delivery.
  • Establish observability, alerting, and performance SLAs for LLM services; collaborate with cross-functional teams to define success metrics and iterate rapidly.

Skills & Qualifications

Must-Have

  • 4+ years engineering experience with 2+ years working directly on LLM / Generative AI projects.
  • Strong Python skills and hands-on experience with PyTorch and HuggingFace / transformers libraries.
  • Practical experience building RAG pipelines, vector search (FAISS / Pinecone / Milvus), and embedding workflows.
  • Experience with fine-tuning strategies (LoRA / adapters) and evaluation frameworks for model quality and safety.
  • Familiarity with Docker, Kubernetes, cloud deployment (AWS / Azure / GCP), and Git-based CI / CD workflows.
  • Solid understanding of prompt engineering, retrieval strategies, and production monitoring of ML services.
  • Preferred

  • Experience with LangChain / LangGraph, agent frameworks, or building tool-calling pipelines.
  • Exposure to MLOps platforms, model registry, autoscaling low-latency inference, and cost-optimisation techniques.
  • Background in productionising LLMs for enterprise use-cases (knowledge bases, search, virtual assistants).
  • Benefits & Culture Highlights

  • Hybrid work model with flexible in-office collaboration and remote days; competitive market compensation.
  • Opportunity to work on high-impact enterprise AI initiatives and shape production-grade GenAI patterns across customers.
  • Learning-first culture : access to technical mentorship, experimentation environments, and conferences / learning stipend.
  • To apply : include a brief portfolio of LLM projects, links to relevant repositories or demos, and a summary of production responsibilities. This role is ideal for engineers passionate about turning cutting-edge LLM research into reliable, scalable enterprise solutions.

    Skills : llm,open ai,gemini

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    Skills Required

    Pytorch, Gcp, Docker, Azure, Python, Kubernetes, Aws

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    Llm • Pune, India

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