Lead Agentic AI Engineer

New

HexionAI, manufacturing

United StatesFull-TimeLead

Salary not disclosed

Apply NowOpens the employer's application page

More jobs in this role

Job Details

Experience: Master’s degree ... with 5+ years of relevant analytics / AI experience, OR Bachelor’s degree ... with 8+ years of relevant analytics / AI experience.
Required Skills: PythonSQLMicrosoft Power BIDatabricksPySpark

Requirements

Have a master’s degree in Mathematics, Computer Science, Data Science, Information Systems, Engineering, or a related field and 5+ years of relevant analytics / AI experience, or a bachelor’s degree in Chemical, Industrial, Computer Science, or a related field and 8+ years of relevant analytics / AI experience.
Have hands-on experience building or consuming MCP servers/clients and exposing enterprise data sources as MCP tools.
Have hands-on experience designing and implementing multi-agent architectures, including orchestrator-executor patterns, tool calling, memory management, and agent coordination.
Have strong Python engineering skills for production AI agents and pipelines, including REST API integration, prompt versioning, evaluation frameworks, and observability.
Have hands-on experience with at least two of Azure AI Foundry, Microsoft Copilot Studio, Microsoft 365 Copilot extensibility, and Microsoft Power BI.
Have strong proficiency in Databricks, including Python, SQL, Delta Lake, PySpark, and notebooks.
Have functional understanding of Supply Planning and/or Manufacturing.
Have experience with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, SD, PM).
Be able to translate business problems into agentic AI solutions and communicate with technical and executive audiences.
Have collaboration and stakeholder management skills for cross-functional environments.
Preferred: experience deploying AI agents in production, including evaluation, safety guardrails, logging, and human-in-the-loop workflows.
Preferred: familiarity with ReAct, Plan-and-Execute, reflection, structured tool outputs, and knowledge graphs or graph databases such as Neo4j.
Preferred: experience in chemicals, manufacturing, or process industries; Palantir Foundry; Azure MLOps; operational KPI frameworks; or Docker, Git, and modern software engineering practices.

Responsibilities

Lead the design, development, and deployment of production-grade AI agent solutions for Supply Planning and Manufacturing.
Architect and build multi-agent AI systems using Azure AI Agent Service, AutoGen, Semantic Kernel, and/or LangChain/LangGraph.
Implement MCP to provide enterprise data as structured context for AI agents in supply chain and manufacturing workflows.
Build generative AI solutions on Azure AI Foundry, including RAG-based knowledge agents, decision support, and document intelligence.
Design AI copilots and topic-based agents in Microsoft Copilot Studio for use through Teams and Outlook.
Scope business problems with stakeholders, define agent capabilities and tool surfaces, prioritize the roadmap, and drive adoption.
Partner with Supply Chain leadership, Demand Planning, Process Engineering, Maintenance Ops, and Plant teams on AI use cases.
Define and maintain agent governance, including prompt versioning, tool auditing, evaluation, observability, and safety guardrails.
Develop on Azure Databricks using PySpark and SQL, Delta tables, notebooks, and Workflows.
Build and maintain Power BI reports and semantic models for AI grounding data and executive dashboards.
Maintain the Supply Chain AI metrics alignment cadence and keep priorities, status, and roadblocks visible to leadership.
Mentor analysts and engineers on agentic AI design patterns, MCP, and AI delivery practices.

View Full Description & ApplyYou'll be redirected to the employer's site