Engineering Manager: Applied AI

What you'll do:

• Build and lead the team. You will lead and grow a squad of senior full-stack engineers building AI-enabled tooling, managing the full lifecycle of hiring, onboarding, and continuous growth through weekly 1:1s and performance feedback. You’ll align individual aspirations with business needs while fostering a culture of high standards and psychological safety.

• Set the charter and direction. Partnering with Engineering leadership, Product, and Design, you will define the team’s ownership boundaries and shape Copia’s applied-AI strategy — translating high-level goals into a clear roadmap and well-scoped delivery milestones, and using product taste to decide where GenAI genuinely improves the experience for our users.

• Ship AI features that matter to customers. You will guide the team to integrate GenAI into Copia’s existing Source Control and DeviceLink products and to improve the experience of the Copia Copilot — shipping high-quality, scalable, well-documented capabilities and measuring their adoption and impact.

• Drive the technical direction. You will oversee the architecture of AI-powered, full-stack systems — frontend experiences, backend services, APIs, and the AI plumbing behind them (LLM integration, RAG pipelines, evaluation, model selection, prompt and context strategies) — and ensure they are reliable and scale. You’ll stay close enough to the technology to provide architectural input, code reviews, and hands-on contributions where they add the most leverage.

• Champion how we build with AI. You’ll help the team make AI coding agents a central part of how they work to increase velocity while maintaining high standards, and you’ll share best practices that raise how the entire engineering organization leverages AI tools.

• Own operational quality and how we work. You’ll be responsible for on-call practices, incident response runbooks, and the engineering standards (from CI/CD to ADRs, testing, and evaluation of AI behavior) that empower the team to move faster with higher confidence in a safety-critical domain.

What we're looking for:

• 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).

• 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.

• 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.

• 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.

• Demonstrated ability to coach engineers — helping them grow technically, take on bigger scope, and develop in their careers.

• 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.

• 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.”

• 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.

• 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.

Bonus points:

• 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 starting or growing a team — defining charter, hiring engineers, and establishing how it works with the rest of the org.

• Experience standing up or improving engineering practices: incident response, on-call, ADRs, code review standards, or career ladders.

• 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.