TalentXM, formerly known as BlockTXM Inc, is seeking an AI Agent Engineer to design and implement production agentic AI systems for manufacturing clients. The role focuses on building AI capabilities that improve operational metrics and collaborating with various stakeholders to ensure successful integration and deployment of AI solutions.
Responsibilities:
- Assess current operations, data, and AI readiness; identify high-ROI use cases
- Deliver a prioritized 90 day roadmap (quick wins plus structural builds)
- Build production agentic systems with LangChain and LangGraph
- Design tool calling, MCP integrations, and guardrails against bad outputs
- Stand up RAG pipelines over manufacturing knowledge (SOPs, work orders, manuals, issue history) with proper evaluation harnesses
- Integrate agents with MES, ERP, CMMS, and data platforms (Snowflake, Databricks)
- Build on Azure, AWS, or GCP; use APIs, webhooks, and integration tools (Workato, n8n, Power Automate) where relevant
- Handle data access, governance, and PII / IP responsibly
- Define measurable success criteria; lead UAT and deployment
- Monitor accuracy, latency, and adoption; troubleshoot in production
- Document architectures, decisions, assumptions, and runbooks in a way that supports async global collaboration
- Contribute reusable templates, prompts, demos, and accelerators to the TalentXM internal library
- Partner with plant leaders, CIO / CDO teams, operations, quality, and maintenance
- Translate manufacturing needs into clear technical and delivery plans
- Advise honestly on where AI should automate work, augment experts, or support a decision without overpromising
Requirements:
- LangChain, LangGraph, and MCP (Model Context Protocol)
- Strong Python, tool calling, and RAG production experience, not just prototypes
- A track record of taking at least one agentic or RAG system to production with measurable outcomes
- Awareness of smart factory / Industry 4.0, OT/IT, MES, ERP, quality, maintenance, and production operations concepts
- Comfortable speaking with both technical teams and business stakeholders
- Strong written communication and async documentation
- Comfort working in global fractional pods and outcome based delivery models
- 5+ years in software / AI engineering, with hands on agentic or LLM systems
- Experience across discrete and/or process manufacturing, or a comparable operational / regulated domain
- Computer vision exposure (visual inspection, defect detection) a plus
- Cloud and data platforms: Azure, AWS, GCP, Databricks, Snowflake
- Integration and automation: Workato, n8n, Power Automate, MuleSoft, Boomi
- Certifications a plus: AWS ML Specialty, Azure AI Engineer, Azure / AWS Solutions Architect, NVIDIA, Databricks, Snowflake, ISA CAP, or Workato Automation Pro. Equivalent hands on project experience accepted when backed by strong examples and references