Engineering Manager (Applied AI)

Join Copia, a leading company in industrial automation, as an Engineering Manager for our Applied AI team. In this role, you will lead a group of full-stack software engineers, define the team's ownership boundaries, ship AI features that matter to customers, drive the technical direction, champion how we build with AI, and own operational quality. You should have hands-on experience building AI-enabled products, strong communication skills, empathy, humility, and high standards. A bachelor's degree in Computer Science or Engineering and 5+ years of professional full-stack software engineering experience are required.

• Lead and grow a team of full-stack engineers to build AI-enabled tooling, managing the full lifecycle of hiring, onboarding, and continuous growth.
• Define the team’s ownership boundaries and shape the applied-AI strategy, translating high-level goals into a clear roadmap and well-scoped delivery milestones.
• Oversee the architecture of AI-powered, full-stack systems, ensuring they are reliable and scalable, and provide architectural input, code reviews, and hands-on contributions.
• Hands-on experience building AI-enabled products — not just using ChatGPT, but shipping applications backed by LLM APIs, RAG, and related GenAI techniques — and the judgment to tell where AI adds durable value versus where it doesn’t
• Strong written and verbal communication. You can adjust your message for engineers, executives, and partner teams without losing the substance, and you can explain complex AI work to non-technical stakeholders
• Empathy, humility, and high standards. You are kind to people and tough on problems
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
• Demonstrated ability to coach engineers — helping them grow technically, take on bigger scope, and develop in their careers
• A strong technical foundation across the stack — frontend, backend, APIs, and data — and the ability to design AI-powered capabilities that are reliable, scalable, and maintainable
• Eagerness to dig into a complex domain. You don’t need to know PLCs on day one, but you should be excited to learn how factories actually run
• 5+ years of professional full-stack software engineering experience, with at least 1–2 years of formal or informal people-leadership experience (tech lead, team lead, or direct management)
• Daily fluency with AI coding tools (e.g., Cursor, Claude Code, or Copilot) and a clear sense of their strengths and weaknesses, plus a track record of helping others get more out of them
• Sound judgment around prioritization, scope, and trade-offs, including knowing when to ship a focused MVP versus investing in the right foundation, and when to say “no” or “not yet.”
• Experience shipping production GenAI features at scale — evaluation frameworks, prompt and context engineering, retrieval pipelines, model selection, or guardrails for safety-critical use
• Deeper ML background: model training or fine-tuning (e.g., a strong Kaggle result or a popular open-source fine-tune), not just consuming AI tooling
• Experience standing up or improving engineering practices: incident response, on-call, ADRs, code review standards, or career ladders
• Experience starting or growing a team — defining charter, hiring engineers, and establishing how it works with the rest of the org
• Experience with some of our stack or adjacent technologies on both sides of the wire: TypeScript / Node.js, React, Go, C#, Python, PostgreSQL, AWS, Datadog
• Experience building developer tools, or working on Git internals, CI/CD, or DevOps platforms
• Background in B2B SaaS, developer tools, industrial automation, OT/IT, manufacturing software, or IoT