Senior AI Software Engineer

Role Overview

AI Application and Agent Development

• Design, build, test, and deploy AI applications and agents using approved commercial or open-source models, tool calling, and workflow orchestration.
• Build retrieval-augmented generation services and a governed NPI knowledge layer for standards, lessons learned, cost models, and project history.
• Develop specialist agents and deterministic workflow components with human review and escalation paths for high-impact decisions.
• Create evaluation, testing, guardrail, monitoring, and cost-management practices for accuracy, reliability, security, latency, and business impact.

Data and Enterprise Integration

• Connect AI applications to approved sources such as PLM, ERP, MES, SharePoint, demand systems, and factory or test data.
• Implement secure APIs, services, connectors, and data contracts that support retrieval, workflow execution, auditability, and maintainability.
• Implement role-based access, data scoping, secrets management, logging, and privacy controls.

Technical Leadership and Delivery

• Own the target architecture, technical roadmap, and build-versus-buy decisions for the NPI AI application ecosystem.
• Establish standards for source control, code review, automated testing, CI/CD, documentation, observability, incident response, and reusable components.
• Lead discovery and delivery planning with analysts and engineering experts, translating workflows into increments, estimates, and acceptance criteria.
• Mentor engineers and technical contributors and communicate tradeoffs to stakeholders.

Required Qualifications

• Bachelor's degree in a relevant computing or engineering field, or equivalent practical experience.
• At least 7 years of software engineering experience, including production application or service architecture and delivery.
• Hands-on experience with LLM-powered or agentic applications, model APIs, tool calling, prompt design, RAG, and systematic evaluation.
• Proficiency in a modern programming language such as Python, C#, or Java, plus API, service, data model, and integration design experience.
• Experience with production engineering practices, enterprise data integration, data pipelines or connectors, SQL, and data quality.

Additional Qualifications

• Demonstrated technical leadership, architectural judgment, and communication with technical and business stakeholders.
• Ability to travel occasionally, up to 10% of the time.
• Manufacturing, engineering, NPI, enterprise knowledge systems, vector search, cloud AI, or governed AI experience is preferred.