Interested in this AI Agent Developer role at FurtherAI?
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About Us
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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, Converge), grown more than XY00% in the last 12 months, and work with some of the largest names in insurance \- top 10 carriers/brokers, F100 \& 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 engineering leader to own our AI organization \- the agents, infrastructure, and products at the core of everything we build.
Why Join Us
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- Outsized ambition: We're out to build the definitive AI company for insurance \- a trillion\-dollar industry \- and we're moving faster than anyone in the space.
- Own the AI org: Lead our AI team and grow it into the engine of the company \- hiring the leaders under you as we scale post\-Series A.
- 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 a huge piece of the company and build a team from the ground up \- ideal if you want to start your own thing one day.
What You'll Do
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- Own and grow the AI org. Lead our AI team today and scale it into three teams \- AI infrastructure (routing \& reliability), Agent intelligence (evals, shared tools, multimodal pipelines), and Agentic products (the customer\-facing AI assistant, long running agentic workflows).
- Set technical direction for how we build agents that hold up in real production, on real customer money.
- Recruit, mentor, and retain a world\-class team of AI engineers \- and hire the team beneath you as the org grows.
- Stay deeply technical. You'll still be in the code and the architecture. You set the bar by example, not from the sidelines.
- Push the frontier of what agents can do for insurance as the field moves.
Representative Projects
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- Model router to operate on the Pareto frontier of speed and accuracy
- Infrastructure for long\-running agents
- A general\-purpose AI assistant that reads documents, pulls from connected systems, and takes actions end to end
What We're Looking For
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- Proven experience leading AI/ML engineering teams building production LLM/agent systems — you've managed engineers and shipped, not just advised.
- Deep, hands\-on understanding of agentic architectures — tool use, planning, multi\-agent orchestration, evals, reliability.
- Strong technical bar — still fluent in the code; can dive deep and evaluate experiment design rigorously.
- Track record building and scaling teams — recruiting strong people and growing leaders under you.
- Clear communicator, in person and in writing.
- Bonus: B2B SaaS and working at a early stage growth startup.
- Above all: drive, grit, and ownership. If you excel here, other requirements are secondary.
At FurtherAI, we set a high bar. We're not looking for someone who just wants a job — we're looking for someone who wants to build something transformative and own a big piece of it. If you thrive where the pace is fast, expectations are high, and the rewards are outsized, you'll love it here.
Benefits
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- Fully covered, best\-in\-class health, dental, and vision
- Competitive compensation, meaningful stock options, company 401(k)
- Unlimited PTO
- Outstanding in\-office culture in the heart of San Francisco
- Lunch and dinner onsite
- Team events \- happy hours and off\-sites
- Pre\-tax commuter benefits
Compensation Range: $300K \- $450K
Salary Context
This $300K-$450K range is above the 75th percentile for AI Agent Developer roles in our dataset (median: $188K across 26 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 3,708 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At FurtherAI, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills in Demand for This Role
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $238,500 based on 58 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($375K) sits 57% above the category median. Disclosed range: $300K to $450K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
FurtherAI AI Hiring
FurtherAI has 1 open AI role right now. They're hiring across AI Agent Developer. Based in San Francisco, CA, US. Compensation range: $450K - $450K.
Location Context
AI roles in San Francisco pay a median of $277,088 across 810 tracked positions. That's 27% above the national median.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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