Principal Engineer

MotorK sits at the intersection of deep vertical complexity - automotive SaaS, 10,000+ dealerships, enterprise-grade requirements - and a company that has gone all-in on AI as its primary engine of scale. We believe vertical SaaS captures the most value from AI, and none of that value is reachable unless the data underneath it is modeled, governed and engineered right.

A senior, deeply technical leader who owns both the direction and the execution of a core area of the SparK platform.

This is not a role that manages managers. You lead a very small, high-calibre team whose capacity is multiplied by AI agents, and you stay hands-on: designing, coding, and reviewing on the critical path. At the same time you carry full leadership accountability for those engineers - their growth, their delivery, and their alignment with the rest of R&D.

You are accountable for the architecture, the delivery, the quality, and for turning AI into measurable engineering leverage rather than experimentation.

• Expert-level command of API design (REST/GraphQL), event-driven architecture, data pipelines, and cloud-native engineering on AWS.
• Proven, hands-on application of AI/LLMs and agentic workflows to real production engineering problems - including designing the guardrails, evaluation, and review process around them.
• Strong reliability and observability practice in high-volume, multi-tenant B2B SaaS.
• Proven people management of a small senior team: objectives, feedback, performance, and career progression - while still contributing technically.
• Effective communication with all stakeholders to keep the team's goals and contribution aligned within the tribe and with external parties.
• Leads cross-tribe initiatives and proactively aligns others on relevant topics.
• Leads by business value and constraints; identifies risk before it materialises; stays sharp on target through vague situations and decides independently.
• Sharp issue analysis: fast triage, continuous filtering of noise vs. signal, effective communication of issues.
• Coacher and enabler - grows people without compromising execution and quality.

• →Own the target architecture. Take a clear-eyed view of the existing stack and make the hard calls on what to rebuild, retire, or scale.
• →Stay hands-on. Review and support the AI Agents work at all levels needed, from  Code review to test definition and any other tasks required to complete the SDLC
• →Build and run the team's AI layer. Put agents to work on code generation, data and schema work, testing, documentation, and self-healing operations — and hold their output to the same review discipline as human output - AI Everything you can
• →Lead the team. Own design decisions, technical refinement, development, testing for a 2–3 person squad; run 1:1s, set objectives, give feedback, and drive the career growth of senior engineers.
• →Coordinate beyond the team. Align peers, product, and stakeholders across tribes on goals, dependencies, and trade-offs; represent the area in cross-R&D initiatives and lead them when the topic is yours.
• →Attack manual, repetitive engineering. Replace bespoke, case-by-case work with agentic solutions.
• →Treat the area as a product. Documented interfaces, self-serve tooling, sandbox, automated certification.
• →Unblock and report. Remove impediments for the team and provide insights supported by Agile/Lean metrics.