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engineering opportunity

FurtherAI - Staff AI Engineer

You will build orchestration and reasoning systems on top of existing LLMs to automate insurance workflows. This involves setting up evaluation harnesses, experimenting with multi-agent techniques, and ensuring reliable production performance.

San Francisco, California, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at YO?

Source: Paraform - https://www.paraform.com/share/furtherai/cms3gcwgi003t0dkw9ymq3vcy · Company: further.ai

Location: On-site, 5 days/week in San Francisco · Full-time · Salary $225K - $350K plus competitive equity · Open to visa transfers (e.g. OPT, H1B transfers), case-by-case basis

About FurtherAI

FurtherAI is building the AI agents that run insurance, a trillion-dollar industry still powered by manual work. Its domain-specific AI Workspace automates workflows like submission intake, policy comparisons and underwriting audits, and supports customers writing over $15B in premiums across all 50 states. Founded in 2024, FurtherAI has raised $30M from investors including Andreessen Horowitz, Y Combinator, Nexus and South Park Commons, and works with top 10 carriers/brokers and F100 and public companies.

Both founders are engineers, and engineers have an outsized say on product direction.

The role

Join the agent team as a Staff AI Engineer and shape both the product and how FurtherAI builds agents. This is not a model-training role: you'll build orchestration and reasoning systems on top of existing LLMs.

What you'll do

Set up end-to-end evals to measure and improve agent performance.

Experiment with new agentic techniques: multi-agent systems, reasoning-from-feedback, and more.

Build lightweight tools, servers and orchestration layers (e.g. MCP servers) that let agents run reliably in production.

Stay on top of emerging research on LLMs/agents and bring ideas into production experiments.

Representative projects

Eval harnesses that measure and lift agent accuracy on real insurance work

Orchestration and tools (e.g. MCP servers) that keep agents reliable in production

Multi-agent systems and reasoning-from-feedback loops

Long-running agents that read documents, pull from connected systems, and take actions end to end

Benefits

Fully covered health, dental and vision benefits

Competitive compensation, meaningful stock options, company 401(k)

Unlimited PTO

In-office culture in San Francisco, lunch and dinner onsite

Team events such as happy hours and off-sites

Pre-tax commuter benefits

8+ years building in ML/AI at a high-growth top tech company

Strong experience with Python

Amazing ability to speak with LLMs (Occam's razor in prompting)

Clear communicator, both in person and in writing

Bonus: background in B2B SaaS and 0-1 experience

Above all: drive, grit and ownership

Which skills does this role require?

PythonMachine learningArtificial intelligencePrompt engineeringSystem architectureB2B SaaSEvaluation frameworksProduction engineeringMachine LearningArtificial IntelligencePromptingAutomationEvaluationProduction systemsData scienceSoftware engineering

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.

Role information can change. Confirm current details on the original application page.

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