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    • Senior Gen AI Engineer – GenAI - Vijaipura - Ampstek

    Ampstek
    Ampstek Vijaipura

    1 week ago

    Default job background
    Description
    Role :: Senior Gen AI Engineer – GenAI / ML (Python, Langchain)
    Location :: Remote/India
    Duration :: Full Time
    Overlap: 4hrs overlap with PST timezone

    Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration.

    Key Responsibilities:

    • Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines.

    • Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions.

    • Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives.

    • Translate business needs into scalable, production-ready AI solutions.

    • Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases.

    • Contribute to architecture discussions, code reviews, and performance optimization.
    Skills Required:

    • Proficient in Python, Langchain, and SQL.

    • Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows.

    • Background in machine learning or software engineering with a focus on system-level thinking.

    • Experience working with cloud platforms like AWS, Azure, or GCP.

    • Ability to work independently while collaborating effectively across teams.

    • Excellent communication and stakeholder management skills.
    Preferred Qualifications:

    • 1+ years of hands-on experience in LLMs and Generative AI techniques.

    • Experience contributing to ML/AI product pipelines or end-to-end deployments.

    • Familiarity with MLOps and scalable deployment patterns for AI models.

    • Prior exposure to client-facing projects or cross-functional AI teams.
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