Senior Data Scientist - Bengaluru / Bangalore - confidential

    confidential
    confidential Bengaluru / Bangalore

    3 days ago

    Full time ₹2,500,000 - ₹5,500,000 (INR) per year *
    Description

    As a Senior Data Scientist, you will lead the development of scalable GenAI-powered systems, designing intelligent workflows that leverage large language models (LLMs), vector-based retrieval, and multi-agent orchestration frameworks. Youll drive solution architecture, mentor junior engineers, and deliver production-ready applications that integrate deeply with business processes and platforms.

    Key Responsibilities:

    Lead the design and deployment of GenAI systems leveraging LLMs, retrieval pipelines, and orchestration frameworks for multi-step task execution

    Architect and optimize prompt workflows, including chaining, templating, and context control, for high-accuracy and cost-efficient solutions

    Build and maintain embedding-based retrieval systems using vector databases and context-aware generation techniques (e.g., retrieval-augmented generation)

    Collaborate with product owners and engineering leads to align solution architecture with business objectives

    Guide and mentor junior engineers on best practices in prompt design, token optimization, security controls, and observability patterns

    Define standards for code modularity, response consistency, prompt safety, and testing across LLM-powered applications

    Maintain strong CI/CD practices using version-controlled workflows and cloud-native deployment pipelines

    Evaluate emerging GenAI tooling and provide technical recommendations for experimentation and adoption

    Qualifications

    4+ years of experience in AI/ML solution delivery, with a strong focus on GenAI or LLM-integrated systems

    Expertise in Python (v3.11+) with deep familiarity in LLM APIs, embedding generation, vector-based search, and modular pipeline design

    Proven experience in building and deploying prompt-driven applications at scale

    Solid understanding of agent orchestration patterns, multi-agent task flows, and context layering techniques

    Hands-on experience in cloud-native delivery (preferably Azure), including containerization, CI/CD, and monitoring

    Preferred Qualifications

    Exposure to model context protocols (e.g., MCP) and agent-to-agent (A2A) coordination concepts

    Experience with LLM observability tools (latency tracking, relevance scoring, cost management)

    Contributor to internal or open-source projects that showcase applied GenAI, workflow orchestration, or prompt libraries

    Understanding of responsible AI guidelines, token-level safety, and enterprise security standards in GenAI applications

    * This salary range is an estimation made by beBee
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