Senior​/AI Engineer — Evals & Model Quality

About Us

At FurtherAI, we’re building the AI agents that run insurance — a trillion-dollar industry still powered by manual work. By combining frontier agentic AI with deep domain expertise, we’re reshaping how the industry’s most critical work gets done.

We’ve raised more than $30M from top investors (Andreessen Horowitz, YC, Nexus, South Park Commons), grown more than XY 00% in the last 12 months, and work with some of the largest names in insurance — top 10 carriers/brokers, Fortune 100 companies, and public companies.

We are a deeply technical company. Both founders are engineers, and engineers have an outsized say on product direction.

Now, we’re looking for an exceptional AI Engineer to own how we evaluate and continuously improve the quality of AI agents across our platform.

• Outsized ambition: We’re out to build the definitive AI company for insurance — and we’re moving faster than anyone in the space.

• Elite team: Founders and engineers from the best companies and schools in the world — ex-Apple AI Research, Brex, Coinbase, and Uber; 4 YC founders and 6 ex-founders; grads of Stanford, Berkeley, IITs, and Cornell.

• Massive market impact: Insurance is the backbone of global commerce. Our work reshapes how the industry operates.

• Founder’s mindset: Own big pieces of the product from day one — ideal if you want to start your own company one day.

• Own evaluations across FurtherAI: Build the evaluation frameworks and infrastructure that measure the accuracy, quality, and reliability of our AI agents across workflows, Assistant, document processing, and computer use.

• Build high-quality datasets: Develop golden datasets, benchmarks, and regression suites, working closely with Forward Deployed Engineers and domain experts to capture real-world insurance tasks and edge cases.

• Evaluate complex agent behavior: Design evaluations for multi-step agent trajectories, tool use, reasoning, and end-to-end task completion — not just individual LLM responses.

• Build automated grading systems: Develop LLM-as-judge evaluations, deterministic graders, human evaluation workflows, and rubrics that accurately reflect real-world quality.

• Make development evaluation-driven: Integrate offline and online evaluations into development and release processes so engineers can measure improvements, catch regressions, and ship confidently.

• Drive model evaluation and selection: Continuously benchmark frontier and open-weight models across accuracy, latency, cost, and reliability. Use results to inform model selection, upgrades, and production releases.

• Build continuous improvement loops: Turn production failures, customer feedback, and agent traces into new evaluation cases and measurable improvements in agent quality.

• Build an end-to-end evaluation framework for FurtherAI agents, measuring success across multi-step workflows, tool calls, and complex insurance tasks.

• Create a library of golden datasets and benchmarks for common insurance workflows, reusable across customer implementations and out-of-the-box AI skills.

• Build an automated benchmarking system that evaluates new frontier and open-weight model releases and identifies the best models for different tasks.

• Develop production evaluation pipelines that detect quality regressions, identify failure patterns, and turn them into actionable improvements.

• 5+ years of software engineering experience, with strong hands-on experience building production AI/ML systems.

• Experience building evaluation frameworks, LLM-based applications, model benchmarking systems, or applied AI infrastructure.

• Strong understanding of modern LLMs, agent architectures, evaluation methodologies, and model performance tradeoffs.

• Strong Python…