AI/ML Engineer LLM & Agentic Systems (Python)

HCL Global Systems Inc.

  • Mason, OH
  • 30+ days ago

    Highlights

    Key Responsibilities Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python Design and implement RAG pipelines over enterprise data using embeddings and vector databases Build multi-step, tool-using agents (planning, execution, memory) using frameworks such as LangChain Integrate AI systems with APIs, backend services, and cloud platforms Establish evaluation, reliability, and performance strategies (accuracy, latency, cost) SKill 4 - Yrs Of Exp - 6+ - vector databases Build multi-step, tool-using agents (planning, execution, memory) using frameworks such as LangChain Integrate AI systems with APIs, backend services, SKill 5 - Yrs Of Exp - 6+ - cloud platforms Establish evaluation, reliability, and performance strategies (accuracy, latency, cost).

    Numbers & Facts

    LocationMason, OH

    Description

    AI/ML Engineer LLM & Agentic Systems (Python)
    Location: MASON, OH Hybrid


    Must Have Skills
    Skill 1 – Yrs of Exp – 10+ - design and build production-grade LLM-powered applications and agentic systems
    Skill 2 - Yrs of Exp – 6+ - End-to-end development of intelligent solutions from architecture to deployment leveraging Python, modern LLM frameworks, and scalable system design
    SKill 3 - Yrs Of Exp - 6+ - Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python Design and implement RAG pipelines over enterprise data using embeddings
    SKill 4 - Yrs Of Exp - 6+ - vector databases Build multi-step, tool-using agents (planning, execution, memory) using frameworks such as LangChain Integrate AI systems with APIs, backend services,
    SKill 5 - Yrs Of Exp - 6+ - cloud platforms Establish evaluation, reliability, and performance strategies (accuracy, latency, cost)

    AI/ML developers We are seeking AI/ML engineers to design and build production-grade LLM-powered applications and agentic systems. This role owns the end-to-end development of intelligent solutions—from architecture to deployment—leveraging Python, modern LLM frameworks, and scalable system design. Key Responsibilities Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python Design and implement RAG pipelines over enterprise data using embeddings and vector databases Build multi-step, tool-using agents (planning, execution, memory) using frameworks such as LangChain Integrate AI systems with APIs, backend services, and cloud platforms Establish evaluation, reliability, and performance strategies (accuracy, latency, cost)

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