About The Role

ABOUT THE ROLE

This is a founding-level AI engineering role at a small, product-focused B2B SaaS pricing platform, sitting at the intersection of LLM infrastructure and high-stakes commercial decisions. You'll own the evaluation systems, feedback loops, and model infrastructure that tie AI-driven pricing recommendations directly to revenue and compliance outcomes. Your work will have immediate, measurable impact on customers from day one.

WHAT YOU'LL DO

Build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth for model quality.
Systematize and automate expert review workflows currently handled manually.
Develop AI personas simulating B2B buying committees and behavioral effects using usage data and call transcripts.
Automate persona training pipelines to replace today's manual processes.
Own LLM routing across providers (Anthropic, Google, etc.) with explicit cost, latency, and quality tradeoffs.
Maintain infrastructure and data residency boundaries, ensuring regional model calls comply with applicable regulations.
Extend the MCP server used by LLM agents so that features are driven agent-first, not just UI-first.
Work within a typed ontology of pricing entities to ensure 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

8+ years of engineering experience with strong, recent production LLM depth.
Proven track record shipping and owning LLM-powered product features end-to-end — from development through production monitoring.
Direct experience building evals and observability for LLM systems, including eval harness creation and prompt baselining against a typed ontology.
Hands-on experience with structured data models (e.g., Pydantic) to produce auditable, typed model outputs.
Experience operating under data residency, SOC 2, and GDPR constraints in domains where correctness is audited (pricing, billing, payments).
Familiarity with LLM tooling platforms such as LangChain, LlamaIndex, Braintrust, or OpenRouter; MCP or LLM agent tooling experience is a plus.
Strong communication skills to explain non-deterministic systems to both technical and non-technical stakeholders.
Ability to thrive in a lean, high-ownership, fast-moving startup environment.
Must be authorized to work in the United States; visa sponsorship is not available.