Senior Platform Engineer

About the role

Alix is automating estate settlement with AI agents that turn a family’s goals into reliable, multi-step work across real financial institutions and services. As a Senior Platform Engineer you will build and operate the services the rest of engineering ships on: the memory layer, the agent framework, and the model serving path that power our agents.

This is a senior individual-contributor role. You will work closely with Engineering and Product leadership, the Infrastructure team, and the Product Engineering pods that build on the platform.

This role is in office at least four days a week in San Francisco. We are not able to sponsor work visas for this position, now or in the future.

What you’ll do

• Build and operate backend and platform services end to end: design, deployment, observability, production support.

• Take responsibility for one platform domain: the memory layer, the agent framework, or the model serving layer.

• Build shared services and internal APIs for Product Engineering; keep the platform stable enough to build on without reading the source.

• Instrument everything: metrics, logs, traces, and alerts tied to SLOs.

• Write and run evals for the platform surfaces you are responsible for, gated in CI.

• Lead design and code reviews; mentor early-career engineers without direct reports.

• Support your code in production, including on-call for the platform tier and incident response with blameless postmortems.

Who you are

Requirements

• Have built and operated backend or platform services in production, including deployment, observability, and support.

• Strong production experience with Node.js and Python.

• Deep hands-on AWS experience.

• Experience at a company operating at significant scale.

• Startup experience; comfortable with ambiguity and speed.

• Deep experience with AI-assisted development workflows (coding agents, AI code review) and have helped a team adopt them.

• Have led architecture and code reviews and mentored early-career engineers.

• Clear, concise writer; strong opinions, loosely held; teamwork, not ego.

Nice to have

• Understanding of model training: data pipelines, fine-tuning, evaluation.

• LLM serving infrastructure: model gateways, rate limiting, fallbacks, cost tracking.

• Fintech, estate planning, or another regulated domain.