Agentic AI Engineer

Texas Instruments•Richardson, TX

21h

About The Position

Texas Instruments is transforming semiconductor manufacturing through AI. This role sits within the Smart Manufacturing Automation (SMA) organization. You will design, build, and operate the agentic AI infrastructure that powers factory intelligence across TI's global fab and assembly/test operations to connect large language models to live manufacturing data systems and enabling rapid decision support at scale.

Requirements

Design, build, and operate agentic AI infrastructure
Connect large language models to live manufacturing data systems
Enable rapid decision support at scale
Architect and deliver multi-agent AI systems using the A2A (Agent-to-Agent) protocol
Build and maintain MCP (Model Context Protocol) servers in Python
Containerize with Docker and deploy on VMs and Kubernetes clusters
Integrate LLM inference into factory workflows
Manage LiteLLM project credentials, budgets, and routing configurations
Develop agent tools that query manufacturing databases (MES, FDC, APC, OEE, etc.)
Design, evolve, and influence the Agent Delivery Framework
Establish and document agentic software development best practices
Build and maintain Knowledge Graph and RAG systems (Neo4j, Vectara)
Collaborate with multiple departments, domain architects, and factory engineers
Present architecture roadmaps and live agent demos to peers and senior manufacturing leadership
Contribute to cross-domain AI access and guardrails governance strategy

Responsibilities

Architect and deliver multi-agent AI systems using the A2A (Agent-to-Agent) protocol, including orchestrator and sub-agent topologies that span multiple factory data sources.
Build and maintain MCP (Model Context Protocol) servers in Python, containerized with Docker and deployed on VMs and Kubernetes clusters; register agents and MCP servers.
Integrate LLM inference into factory workflows; manage LiteLLM project credentials, budgets, and routing configurations.
Develop agent tools that query manufacturing databases (MES, FDC, APC, OEE, etc.) and expose clean interfaces for downstream AI consumption.
Design, evolve, and influence the Agent Delivery Framework.
Establish and document agentic software development best practices; create reusable agent templates adopted across business teams.
Build and maintain Knowledge Graph and RAG systems (Neo4j, Vectara) to enable document and parametric data retrieval across thousands of manufacturing documents and records.
Collaborate with multiple departments, domain architects, and factory engineers to identify high ROI agent use cases, prioritize delivery, and ensure agents meet security and authentication requirements.
Present architecture roadmaps and live agent demos to peers and senior manufacturing leadership.
Contribute to cross-domain AI access and guardrails governance strategy.