1 month ago
Base Salary
$225k - $255k/yr
Responsibilities
- Build evaluation harnesses and benchmarks using tracked pricing outcomes as ground truth.
- Automate expert review workflows and persona-training pipelines that are currently manual.
- Develop AI personas simulating B2B buying committees and behavioral effects from usage data and call transcripts.
- Own LLM routing across providers while balancing cost, latency, and quality.
- Maintain infrastructure and data-residency boundaries, including EU-only model calls where required.
- Extend the MCP server for LLM agents, including customer-facing agents, and define feature completion around agent-driven capabilities.
- Maintain structured, auditable model outputs through a typed ontology of pricing entities.
- Identify and remediate latency, data drift, and cold-start issues in the pricing loop.
Requirements
- 8+ years of engineering experience with strong, recent production LLM depth.
- Proven experience shipping and owning LLM-powered product features in production.
- Hands-on experience building evaluations and observability for LLM systems.
- Experience with MCP or with building tools and integrations for LLM agents.
- Familiarity with LangChain, LlamaIndex, Braintrust, or OpenRouter.
- Experience operating under data residency, SOC 2, and GDPR constraints in audited, high-stakes domains.
- Strong communication skills for explaining non-deterministic systems to clients, partners, and pricing experts.
- Ability to scope pragmatic product-engineering solutions and deliver in a lean startup environment.
- Authorized to work in the US.
- Preferred: experience evaluating AI pricing recommendations using historical pricing outcomes as ground truth.
- Preferred: background in SaaS pricing, revenue operations, or another high-stakes revenue-impact domain.
Benefits
- Early-stage equity commensurate with a founding-team role.
- High-impact, high-ownership position with direct influence over product and technical direction.
- On-site role in San Francisco, California; candidates should be based in or willing to relocate to the San Francisco Bay Area.