Full Stack Engineer

Storm2's client is an early-stage Insur Tech company rebuilding commercial insurance distribution from the ground up. They're growing rapidly, adding around 1,000 customers per month, and have scaled more than 100x over the past year by using AI to automate work that has historically required large teams of brokers, service agents, and underwriters.

Their view is simple: commercial insurance is still overwhelmingly human-led, and there is a huge opportunity to turn operational judgement into software.

A lot of AI engineering roles are really experimentation roles. This isn't one of them.

You'll be shipping production systems that directly impact revenue, conversion, underwriting efficiency, and customer experience. The people building the product sit alongside the operators using it every day, so you'll see problems firsthand and have the autonomy to solve them.

This is a role for someone who moves comfortably between frontend, backend, and AI systems.

Someone who cares about whether the metric moved, not whether the architecture diagram looked elegant. You'll work closely with founders, ship fast, measure outcomes, and iterate quickly when something isn't working.

• Building AI-powered product features across the full stack
• Designing and deploying agent workflows, LLM applications, and automation systems
• Working directly with sales, service, and underwriting teams to identify operational bottlenecks
• Creating feedback loops, evaluations, and decision-tracing systems that continuously improve model performance
• Testing and implementing new AI capabilities as models and tooling evolve
• Shipping production code rapidly and measuring business impact
• Owning outcomes such as conversion, efficiency, and user adoption metrics
• Presenting results and learnings to both technical and non-technical stakeholders

• 5+years of software engineering experience
• Experience shipping production software systems
• Strong engineering skills in Python, Type Script, or similar languages
• Experience building and deploying AI-powered products, including LLM applications, agents, or workflow automation
• Ability to work across frontend, backend, and AI infrastructure layers
• A track record of moving quickly from concept to production
• Comfort working directly with business stakeholders and translating operational problems into software solutions
• Strong product instincts and a focus on measurable business outcomes
• Willingness to be based in San Francisco or relocate

• Voice AI or real-time systems experience
• Experience with RAG architectures, agent frameworks, or evaluation systems
• Background building internal operations platforms, sales tooling, or workflow automation products
• Previous startup experience, particularly in high-growth environments

The people who do well here are naturally curious about how businesses actually operate. They spend time with end users, spot inefficiencies before they're reported, and use AI to remove friction from critical workflows.

If you're already using tools like Cursor, Claude Code, or similar AI-assisted development environments as part of your daily workflow, and you've shipped AI products that real customers depend on, you'll likely find this environment familiar.