# Founding AI Engineer at Clera

Founding AI Engineer at Clera in San Francisco. On-site, full-time, paying $225k–$255k. Posted August 1, 2026.

- Company: Clera
- Location: San Francisco
- Workplace: On-site
- Job type: Full-time
- Pay: $225k–$255k
- Experience: 8+ years
- Posted: 2026-08-01
- Apply: https://jobs.ashbyhq.com/clera/be9768a3-26e9-4312-a13f-3ebd9595e044/application
- Source: https://jobmagic.ai/jobs/founding-ai-engineer-clera-kfag22

## Requirements

- 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. Visa sponsorship is not available for this role.

## Description

### About the Role

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 **Founding AI Engineer**, 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 one and expected to own outcomes end-to-end.

### What You'll Do

- 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 ontology 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.

### What We're Looking For

**Required**

- 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. **Visa sponsorship is not available for this role.Nice to Have**

- 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.

### Compensation & Benefits

- **Base salary:** $225,000 – $255,000 USD annually

- Early-stage equity commensurate with a founding-team role

- High-impact, high-ownership position with direct influence over product and technical direction

### Location

This role is **on-site in San Francisco, CA**. Candidates should be based in or willing to relocate to the San Francisco Bay Area.