AI Platform Engineer

Katapult Labs

4h•Remote

About The Position

We're hiring a Senior–Staff AI Platform Engineer to be the first dedicated engineering hire embedded inside one of our clients a US-based, early-stage AI startup building AI for deal and contract workflows (starting in real estate and expanding toward a broader contracts/HR platform). The product is AI-heavy: a chat-first interface layered over document review, deal timelines, and next-step recommendations, powered by a mix of LLMs and classic/deterministic ML. This is not a research or pure model-training seat. We're looking for a builder with high agency who ships production software and operates LLM/ML systems in the real world. You'll build day-to-day with AI coding tooling (Claude Code, Codex CLI) that's how the team works and you'll own the reliability, observability, and quality of AI features in production.

Requirements

Strong software engineering background you've built and run scalable, cloud-native SaaS in production (not just notebooks).
Hands-on experience running LLMs / AI systems in production: prompting, evaluation, observability, monitoring.
AI-native workflow fluency you build with AI coding tools every day and know how to drive them, not take orders from them.
Solid Python and comfort across the stack (backend-leaning is fine).
Experience with data pipelines and ML/AI infrastructure on GCP or AWS.
Strong written and spoken English; comfortable operating on US hours and embedded in a client team.

Nice To Haves

GCP specifically the platform is migrating from AWS toward Google Cloud.
Eval frameworks, experimentation, and cost-tracking tooling.
Consultancy / multi-hat background comfort adapting fast in an early-stage, shifting environment.
Fintech, legal-tech, or document-heavy domain exposure.
Model training / fine-tuning genuinely a plus, not a requirement. We're optimizing for production engineering + LLM-ops over model-training depth for this hire.

Responsibilities

Design, build, and maintain scalable ML, AI, and data-platform services that power production features end-to-end.
Operate LLM applications in production: chat with memory, retrieval, prompt management, versioning, and experimentation.
Build and run structured evaluation pipelines (golden datasets, regression checks) so changes ship with confidence.
Own AI/ML observability and monitoring instrument, trace, and debug model behavior in prod with tools like Langfuse or MLflow (knowing one is enough).
Integrate and serve LLM-agnostic model backends (e.g., Anthropic models via Bedrock and Vertex) and support deterministic/custom ML where open-source models fall short (e.g., document/PDF parsing).
Contribute to data lineage, governance, and compliance as the platform matures.
Partner closely with product and the broader team to move fast without breaking quality.