Senior Backend / Product Engineer (AI Platform)
About The Position
We’re hiring a senior backend-first product engineer to help build and scale our AI-powered cost intelligence platform. This role is explicitly product-focused. You will not be pulled into client delivery. Your mission is to build core platform capabilities that mature our current FinOps platform into a smart intelligence platform - including AI-driven insights, workflows, and agent-based features that can be sold as standalone capabilities. You’ll operate with high autonomy, significant ownership, and direct access to product leadership. Think founding engineer energy, without the chaos. You will help define how AI capabilities move from experimentation to durable product features, with an emphasis on reliability, cost efficiency, and clear user value - not just model novelty.
Requirements
- 5+ years professional software engineering experience
- Strong backend engineering background (full-stack a plus, not required)
- Hands-on experience building on AWS
- Strong proficiency in Python (Java/C++ acceptable as secondary languages)
- Demonstrated experience using AI in real production systems (not just experimentation - clear, repeatable patterns)
- Comfortable working in ambiguity with product-led direction
- Ability to architect backend services that support asynchronous workflows, event-driven pipelines, and AI agents that operate over time rather than single request/response cycles.
- Comfort articulating why certain AI approaches were not used, including trade-offs around latency, explainability, data availability, or long-term maintainability.
Responsibilities
- Design and build backend-heavy platform features for our platform
- Productionalise AI-enabled capabilities (e.g. anomaly detection, recommendations, agent-based workflows)
- Implement AI thoughtfully across the entire SDLC - prototyping, testing, iteration, and deployment
- Collaborate closely with Product to turn vision into shipped features
- Identify blockers early, communicate clearly, and iterate fast
- Help shape engineering standards and patterns as the product matures
- Design systems that support model evaluation, prompt/version management, and deterministic fallbacks to ensure AI-driven features are observable, testable, and production-safe.
- Build AI features with explicit evaluation criteria, feedback loops, and guardrails (accuracy, latency, cost, and explainability) so models improve predictably over time.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
51-100 employees
