As an Engineer on Perform & Insights Coach, you'll build AI-powered coaching experiences that help managers and employees turn insights into confident action—directly supporting Culture Amp's mission to create a better world of work.
Coach combines People Science and AI to deliver a personalised coaching assistant, and is being implemented across the Culture Amp platform (including Engage/Perform touch points).
You'll join a cross-functional product team in Coach, working with product, design, data science, and platform partners to evolve a trusted, secure coaching experience grounded in proven methodologies and evidence.
You will collaborate closely with a dedicated front-end engineer to balance the team's overall skills while contributing across the full stack where needed.
Build and ship features end-to-end—discovery, implementation, testing, launch, iteration—primarily in Python for Coach services, and step into TypeScript/React/Next.js UI work when it helps unblock outcomes.
Implement robust APIs and integrations that power Coach's unified, streaming chat experiences, focusing on clear contracts, reliability, and observability.
Use type-safe BFF patterns (e.g., Next.js API routes) to deliver resilient data flows between back end services and front end apps, reducing integration defects.
Contribute to AI-enabled product capabilities (e.g., RAG, agent/tooling integration, evaluation signals) with strong safety, privacy, and telemetry practices.
Improve reliability and performance with careful handling of streaming, token efficiency, idempotent endpoints, and production monitoring/alerting.
Raise the bar for quality through pairing, thoughtful code reviews, small design docs/RFCs, pragmatic testing, and leaving systems better than you found them.
Proven technical ability delivering features in production services using Python (FastAPI or similar), with good fundamentals in testing, observability, and operational hygiene.
Full-stack capability and willingness to jump where needed—comfortable collaborating in TypeScript/React/Next.js and adopting shared front-end patterns and components when it accelerates delivery.
Practical familiarity with AI product development (or a strong desire to learn): integrating RAG/agents/tooling, prompt work, and guardrails/evals into product workflows with a safety-first mindset.
Ability to break down tasks, communicate trade-offs, and work independently while keeping collaborators aligned—bringing clarity in ambiguous spaces consistent with expectations at this level.
Clear, kind communication and strong collaboration with engineers, product managers, people scientists, designers, and data scientists.
A pragmatic problem solver who enjoys decomposing ambiguous problems and iterating toward outcomes.
Comfortable working across the stack—happy to dive into Python services, data models, and infra touch points, and to pair with FE on integration/UI details when helpful.
Curious and AI-interested, motivated by shipping trustworthy features that improve how people work.
A supportive teammate who learns fast through feedback, mentors peers through pairing/code review, and invests in team health and sustainable quality.
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