Scan your resume against ATS criteria for this Founding AI Engineer role at Clera.
We're a small, product-focused team building an AI-powered B2B pricing platform that helps companies continuously optimize their pricing strategies — from packaging design and willingness-to-pay analysis to real-time deal guidance and discount governance. As our
, you'll own the evaluation systems, feedback loops, and LLM infrastructure that allow our pricing AI to earn trust and drive measurable revenue impact.
This is a high-ownership, founding-team role. Your work directly ties model outputs to revenue and compliance constraints in high-stakes B2B pricing decisions. You'll be shipping to real customers from day and expected to own outcomes end-to-end.
Build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth.
Systematize and automate expert review workflows that are currently done manually.
Develop AI personas that simulate B2B buying committees and behavioral effects using usage data and call transcripts.
Automate persona training pipelines that are today manual.
Own LLM routing across providers (Anthropic, Google, etc.) with explicit cost, latency, and quality tradeoffs.
Maintain infrastructure and data residency boundaries (e.g., ensure EU model calls remain in the EU).
Extend the MCP server used by LLM agents — including customer-facing agents — so features are agent-driven.
Define "done" as when agents can drive features through MCP, not just when a UI renders them.
Work within a typed of pricing entities so model outputs are structured and auditable.
Identify and remediate systemic latency, data drift, and cold-start issues in the pricing loop.
8+ years of engineering experience with strong, recent production LLM depth.
Proven track record shipping and owning LLM-powered product features in production — not just dashboards or research prototypes.
Direct hands-on experience building evals and observability for LLM systems.
Experience with MCP or building tools/integrations for LLM agents.
Familiarity with platforms such as LangChain, LlamaIndex, Braintrust, or OpenRouter.
Experience operating under data residency, SOC 2, and GDPR constraints in domains where correctness is audited (pricing, billing, payments, or similar).
Strong communication skills — able to explain non-deterministic systems clearly to clients, partners, and pricing experts.
Product-engineer instincts: able to scope pragmatic solutions and deliver under ambiguity in a lean startup environment.
Authorized to work in the US.
Experience building evaluation harnesses specifically for AI pricing recommendations using historical pricing outcomes as ground truth.
Background in SaaS pricing, revenue operations, or a high-stakes revenue-impact domain.
Early-stage equity commensurate with a founding-team role
High-impact, high-ownership position with direct influence over product and technical direction
This role is
. Candidates should be based in or willing to relocate to the San Francisco Bay Area.
Build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth.
Systematize and automate expert review workflows that are currently done manually.
Develop AI personas that simulate B2B buying committees and behavioral effects using usage data and call transcripts.
Automate persona training pipelines that are today manual.
Own LLM routing across providers (Anthropic, Google, etc.) with explicit cost, latency, and quality tradeoffs.
Maintain infrastructure and data residency boundaries (e.g., ensure EU model calls remain in the EU).
Extend the MCP server used by LLM agents — including customer-facing agents — so features are agent-driven.
Define "done" as when agents can drive features through MCP, not just when a UI renders them.
Work within a typed of pricing entities so model outputs are structured and auditable.
Identify and remediate systemic latency, data drift, and cold-start issues in the pricing loop.
8+ years of engineering experience with strong, recent production LLM depth.
Proven track record shipping and owning LLM-powered product features in production — not just dashboards or research prototypes.
Direct hands-on experience building evals and observability for LLM systems.
Experience with MCP or building tools/integrations for LLM agents.
Familiarity with platforms such as LangChain, LlamaIndex, Braintrust, or OpenRouter.
Experience operating under data residency, SOC 2, and GDPR constraints in domains where correctness is audited (pricing, billing, payments, or similar).
Strong communication skills — able to explain non-deterministic systems clearly to clients, partners, and pricing experts.
Product-engineer instincts: able to scope pragmatic solutions and deliver under ambiguity in a lean startup environment.
Authorized to work in the US.
Experience building evaluation harnesses specifically for AI pricing recommendations using historical pricing outcomes as ground truth.
Background in SaaS pricing, revenue operations, or a high-stakes revenue-impact domain.
Early-stage equity commensurate with a founding-team role
High-impact, high-ownership position with direct influence over product and technical direction
This role is
. Candidates should be based in or willing to relocate to the San Francisco Bay Area.
How to apply for Founding AI Engineer at Clera?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
8+ yrs of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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