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    Job · 17386929

    Platlap Solutions logo

    Generative AI Engineers - PAN India

    Platlap Solutions · Remote · hybrid · Posted 38d ago

    Undisclosed5–7 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Generative AI Engineer (5-7 Years)


    Role Overview


    We are looking for a Generative AI Engineer to build, optimize, and productionise cutting-edge AI systems. You will focus heavily on backend AI orchestration, framework integration, and model performance. In this role, you will take advanced RAG workflows and multi-agent concepts and turn them into scalable, production-grade enterprise software.


    Key Responsibilities

    • AI Orchestration: Build, test, and optimize bespoke Agentic AI solutions and multi-agent workflows.
    • Core Product Integration: Co-develop integration pipelines to embed core AI models into client environments.
    • Technical Delivery: Own the technical lifecycle of AI applications from rapid prototype to stable production release.
    • Optimization & Debugging: Perform technical debugging, root-cause analysis, and latency/prompt optimizations.
    • Best Practices: Implement engineering best practices for LLM evaluation, guardrails, and version control.
    • Risk Management: Identify and flag model drift, data leakage, and system risks early.

    Technical Requirements

    • GenAI Ecosystem: 2+ years of hands-on experience building production RAG pipelines and multi-agent systems using LangChain, LangGraph, or LlamaIndex.
    • Protocols & Frameworks: Strong understanding of Model Context Protocols (MCP), A2A protocols, and Agent Developer Kits.
    • LLM Engineering: Practical proficiency in prompting techniques, fine-tuning workflows, and evaluating LLM outputs.
    • Data Science Stack: Strong hands-on experience leveraging Python, pandas, scikit-learn, and PyTorch.
    • Cloud & MLOps: Experience deploying and scaling machine learning solutions on AWS, Azure, or GCP.
    • DevOps & Containers: Working knowledge of Docker, Kubernetes, CI/CD pipelines, and GitHub Actions.
    • Backend Stack: Production-grade backend coding skills in Python, with basic familiarity in JavaScript/TypeScript for API integrations.

    Sourced from naukri

    Skills

    Retrieval Augmented GenerationMCPLarge Language Models (LLMs)Python

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