Clera
This is a founding-level AI engineering role at an early-stage B2B SaaS pricing intelligence startup based in San Francisco. You'll be one of the first engineers on a small, product-focused team — joining at a formative moment to shape the technical direction of an AI-powered pricing platform used in high-stakes B2B deals.
Your work sits at the intersection of LLM infrastructure, evaluation systems, and revenue-critical product outcomes. You'll build the feedback loops, eval harnesses, and agent tooling that allow a pricing AI to earn trust, remain auditable, and drive measurable business impact for customers.
Design and build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth, supporting release gating against a typed ontology of pricing entities.
Systematize and automate expert review workflows currently performed manually.
Develop AI personas that simulate B2B buying committees and behavioral effects, leveraging usage data and call transcripts.
Automate persona training pipelines that are today manual processes.
Own LLM routing across providers (e.g., Anthropic, Google) with explicit cost, latency, and quality tradeoffs.
Maintain infrastructure and data residency boundaries (e.g., ensuring EU model calls remain within the EU; SOC2/GDPR compliance).
Extend the MCP server used by LLM agents — including customer-facing agents — so that features are agent-driven, not just UI-rendered.
Work within a typed ontology of pricing entities (e.g., Pydantic models for SKU, Proposition, Persona, Quote) so model outputs are structured and auditable.
Identify and remediate systemic latency, data drift, and cold-start issues in the pricing loop.
Dealbreakers
8+ years of engineering experience with strong, recent production LLM depth — including shipping and owning LLM-powered features end-to-end after launch.
Must be authorized to work in the United States; visa sponsorship is not available.
Hands-on experience building evals and observability for LLM systems — creating eval harnesses, baselining prompts, and supporting release gating.
Required
Experience owning LLM infrastructure, including routing across multiple model providers with cost, latency, and quality tradeoffs.
Proficiency with structured data models and typed ontologies (e.g., Pydantic) to ensure model outputs are structured and auditable.
Full end-to-end ownership of LLM-powered features — from development through production monitoring.
Strong communication skills to explain non-deterministic systems to non-technical clients and stakeholders.
Product-engineer instincts: ability to scope and deliver pragmatic solutions in a fast-moving environment.
Nice to Have
Experience with MCP or building tools/integrations for LLM agents.
Familiarity with platforms such as LangChain, LlamaIndex, Braintrust, or OpenRouter.
Experience in domains where pricing, billing, or payments accuracy and auditability are required.
Familiarity with data residency or compliance controls (SOC2, GDPR).
Salary: $225,000 – $255,000 USD annually
Founding-team equity opportunity at an early-stage, high-growth startup
This role is on-site in San Francisco, CA. Candidates must be based in or willing to relocate to the San Francisco Bay Area.
Be cautious! Do not send money to a potential employer. Do not pay any money for a potential contract of employment or for pre-employment training.
About the Role This is a founding-level AI engineering role at an early-stage B2B SaaS pricing intelligence startup based in San Francisco. You'll be one of the first engineers on a small, product-focused team — joining at a formative moment to shape the technical direction of a