Strala — Forward Deployed Engineer

Type: Full-time | On-site | San Francisco, CA Compensation: $150,000–$225,000 + Competitive equity Hiring count: 1 Visa sponsorship: Yes — H-1B Reports to: CTO

About Strala

Strala is rebuilding the foundation of the world's largest industry — insurance — as an AI-native claims operator that automates the entire claims process from intake and fraud detection through settlement, combining automation with human expertise to improve loss ratios, cut manual work, and deliver better outcomes across the claims lifecycle. In under a year the team has reached multi-seven-figure ARR, growing 50% month over month. Backed across two rounds by Tier 1 funds, including Peter Thiel's Founders Fund (led by the partner who was early in OpenAI, Cognition, and Scale AI).

Founded: 2025 | Team size: 11–50 | Total funding: Two rounds (amount not disclosed) Industry: FinTech / Insurance (AI-native claims) Website: strala.ai Office: San Francisco, CA

Team pedigree: Harvard, Berkeley, Oxford; prior experience at Optiver, AMD, and Palantir; ICPC and NeurIPS backgrounds.

Why Candidates Should Join

• Top-quartile comp: Top-quartile salary and equity, plus full relocation support, all meals covered, and productivity tools provided.
• Shape the company and the industry: Redefine claims for the world's largest industry from the ground up.
• More than a deploy role: More technical and product-owning than the average FDE — you shape what the product becomes based on what works in production.
• Build a new function: Work directly with the CTO and join a forward-deployed function still being built (currently one FDE on staff).

Intake Call Summary

• No intake call transcript available on the role page — only an intake video placeholder is present (no transcript to summarize). Pull intake notes separately if needed.

The Role

Deploy multi-modal, agentic AI systems into production for senior insurance stakeholders, owning client deployments end-to-end from scoping through go-live as the primary point of contact — and shaping the product based on what works in production.

What You'll Be Doing

• Individually deploy multi-modal, agentic AI systems into production for senior client stakeholders
• Own client deployments end-to-end, from scoping through go-live, as the primary point of contact
• Build and manage client relationships — understanding challenges, aligning priorities, and becoming the trusted partner executives rely on to scale AI adoption
• Design, build, and evolve AI agents that deliver optimal claims outcomes: prompt engineering, model integration, blitz prototyping using AI-assisted coding tools
• Scope and develop new features that let customers scale while consistently improving claims results
• Integrate Strala's product into client environments, working hands-on with their tech teams on APIs and systems
• Coordinate with the core platform team to ensure smooth delivery and feed actionable insights back into the product
• Capture and share best practices in internal playbooks to scale Forward Deployed Engineering

Tech stack: Python, APIs, cloud platforms, modern AI/ML tooling, LLMs, agentic AI, AI-assisted dev tools

Requirements

• 2+ years technical + client-facing ownership — via agent engineering, forward-deployed engineering, growth engineering, or founding engineer/founder experience
• Python, APIs, cloud, modern AI/ML tooling
• LLM, prompt engineering, agentic AI fluency
• AI-assisted dev workflows daily
• Founder-mode operator
• SF in-person

Green Flags

• Prior Forward Deployed Engineer at a top AI or enterprise platform company. Direct experience deploying agents end-to-end is the highest-signal background.
• Backend engineer who pivoted to a solutions engineer role. The order matters — backend depth first, then client-facing — because the role requires real building, not just integration support.
• Founding engineer or founder background. The role requires founder-mode ownership, jumping between client calls and code without friction
• Strong communications under pressure. Can hold their own with senior insurance executives paying seven figures, present clearly, and translate technical depth into business outcomes.
• ICPC, NeurIPS, or comparable competitive technical pedigree. Aligns with the broader team's bar.

Red Flags

• Pure solutions engineer with no prior backend experience. Radhik flagged this directly — the role requires real building depth, not integration-only.
• Backend engineer with no client-facing experience. The role is half client management, half engineering. Pure builder profiles will struggle.
• Career FDE looking for a polished, mature function. This is a new function being built — currently 1 FDE on the team.
• Not founder-mode. Candidates who need detailed direction or hand-offs will not match the operating bar.
• Cannot or will not relocate to SF. Non-negotiable, even with full relocation support offered.

Role Details

Salary$150,000–$225,000EquityCompetitive equityOn-site policyOn-site, San Francisco (full relocation support)Visa sponsorshipH-1BEmployment typeFull-timeLocationSan Francisco, CA

Screening Questions

• None provided on the role page.

Interview Process

Stage 1 — Application Review Stage 2 — Cultural Fit Interview (Armando) Stage 3 — Cultural Fit Interview (Radhik) Stage 4 — First Technical Interview — assigned from an interviewer pool (Senbo, Georgii, Robin, John, Anish, Rahul, Ananta, Lucas, or a general technical round) Stage 5 — Second Technical Interview — assigned from an interviewer pool (Dom, Sebestien, Abhay) Stage 6 — Final Interview, Strategy/Ops (Lukas and Paul) Stage 7 — Offer Extended Stage 8 — Candidate Hired — Candidate accepts and starts.

(The role page lists 20 raw pipeline stages, most of which are parallel "First/Second Technical Interview with [name]" interviewer slots rather than sequential steps. Collapsed here into the actual sequential flow.)

Ideal Companies & Backgrounds

Not provided as a dedicated section on the role page. Companies named within Nice-to-Have / Green Flags as high-signal FDE backgrounds: Palantir, Anthropic, OpenAI, Scale, Cognition.

Ideal Candidate Profiles

None provided on the role page.

Rejected Candidate Feedback

None provided on the role page.