Lead Gen AI/Data Science Engineer

TekPioneers - A TekGence Company

  • Jersey City, New Jersey
  • 15 days ago

    Highlights

    Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems. • Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches.

    Numbers & Facts

    LocationJersey City, New Jersey

    Description

    Lead AI Engineer with strong software engineering foundations and hands-on experience in Generative and Agentic AI.

    • Architect and Design production-ready applications leveraging Generative AI and agentic AI frameworks.
    • Build, Deploy and Monitor intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines.
    • Integrate new AI applications with traditional pre-existing applications.
    • Implement prompt engineering strategies, retrieval-augmented generation (RAG), and contextual memory systems.
    • Implement various AI coding techniques (context-driven, spec-driven development etc.).
    • Architect and implement AI agents capable of reasoning, planning, and multi-step task execution.
    • Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems.
    • Provide mentoring and technical guidance to developers and other AI Engineers.
    • Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems.
    • Optimize latency, cost efficiency, and scalability of AI-powered workflows.
    • Collaborate with product managers, data teams, and software engineers to deliver AI features.
    • Ensure reliability through testing, logging, monitoring, and observability of AI behavior.
    • Own architectural decisions, coding standards, and best practices.
    • Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches.
    • Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows.
    • Support implementation of governance controls related to data handling, model behavior monitoring, and risk mitigation.
    • Research emerging AI tools and frameworks to continuously improve system capabilities.
    • Document AI workflows and maintain reproducible engineering processes.

    Similar Jobs