FurtherAI - Staff AI Engineer
At a glance
Senior AI Engineering role at deCircle. San Francisco · $225,000–$350,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build end-to-end tests that track agent performance and help improve accuracy on insurance tasks
- Try approaches such as multi-agent setups and feedback-based reasoning, then bring useful ideas into production
- Create lightweight tools, servers and orchestration layers that help agents run reliably
- Follow new LLM and agent research and test relevant ideas in production
What you bring
- At least eight years building in machine learning or AI at a high-growth technology company
- Strong Python skills
- You can explain ideas clearly in conversation and in writing
Who this fits
This senior role suits an experienced AI engineer focused on agent systems built on existing LLMs, rather than model training. You’ll work on-site in San Francisco five days a week. Visa transfers may be considered case by case.
From the employer
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