# FurtherAI - Staff AI Engineer at deCircle

> Onsite · United States · Staff · ML / AI · open. Source: https://alderhq.app/jobs/recruitee%3Adecircletalentpartner%3A2780322 (read 2026-11-08).

## Facts (observed)

- Company: [deCircle](https://alderhq.app/companies/decircle)
- Location text: San Francisco, California, United States
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco, California, United States")
- Posted: 2026-10-12 (27 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://talent.makerdao.network/o/furtherai-staff-ai-engineer
- Skills listed (inferred): Python, LLMs

## Pay and sponsorship

- Posted pay: $225k–$350k per year (from the description)
- Market band for similar posted roles (SF Bay Area, n 174): p25 $248k, median $275k, p75 $300k

## Description (the employer's text)

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

### Requirements

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

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/recruitee%3Adecircletalentpartner%3A2780322 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.