Forward Deployed AI Engineer

Accelerant is a data-driven risk exchange connecting underwriters of specialty insurance risk with risk capital providers. Accelerant was founded in 2018 by a group of longtime insurance industry executives and technology experts who shared a vision of rebuilding the way risk is exchanged – so that it works better, for everyone. The Accelerant risk exchange does business across more than 20 different countries and 250 specialty products, and we are proud that our insurers have been awarded an AM Best A- (Excellent) rating. For more information, please visit www.accelerant.ai.

We're building an AI-powered operating system for how work gets done at Accelerant – across Actuarial, Finance, Legal, Ops, Risk & Compliance, Underwriting, and every function in between. You'll own what gets built, weigh in on what gets bought, and what gets automated out entirely.

This role exists now because we're past the "prototyping" phase. We need someone who can turn the best ideas and prototypes into productionized shipped solutions whether they are custom AI apps, agents, skills/plugins or automating workflows.

You’ll partner closely with Business teams to identify the biggest sources of manual grind, automate them using modern AI and workflow tools, and scale proven solutions across the enterprise. You'll own end-to-end delivery — from technical architecture decisions (orchestration frameworks, RAG patterns, vector stores, agent design) to production code to operational reliability. You'll have the tools, the cloud budget, and the autonomy to actually do it.

• You see an inefficient process and can't leave it alone. You believe in quick iterations and working towards building the right solutions.
• You've shipped AI-enabled solutions into production
• You've been building with LLMs, agents, coding assistants, and workflow tools long enough to have strong opinions about what’s real and what’s hype.
• You can vibe code prototypes for business alignment and immediately transition to building for production
• Tries new AI tools the week they drop and have the browser history to prove it.
• You operate with autonomy. You can carry a technical discussion on tech stack choices, tradeoffs, and are genuinely curious about leveraging emerging technology.

• You will work directly with key stakeholders in a consultative manner to identify pain points and start building solutions to simplify manual and redundant workflows. You write the production code — this isn't a strategy role. You will build towards automation and agentic capabilities.

• Partner with function heads to design, test, and deploy AI-driven agents and workflow automations. You own evals, observability, guardrails, and the "is this thing actually working" layer. Success means measurable outcomes — hours reclaimed, error rates reduced, processes that used to take days running in minutes.

• Use AI coding assistants (e.g. Claude, Replit, Vercel, etc.), low/no-code platforms, and workflow automation tools to rapidly build and ship MVPs. You pick the fastest path to a working solution. You also own cloud infrastructure, CI/CD, and operational reliability for what you ship.

• When internal builds aren’t the right choice (i.e., due to feasibility, speed to market, costs), lead vendor evaluations, negotiate modular solutions, and ensure clean integration with our data and AI platforms.

• Shipping a tool is the easy part. Getting people to change how they work is hard. You'll lead the education, documentation, and change management that makes adoption happen.

·       Shipped LLM-powered products in production (Python/TypeScript, orchestration frameworks, RAG)

• Fluent with evals, observability, and guardrails — knows how to tell when AI is failing silently
• Can prototype and productionize — not one or the other
• Operates autonomously, communicates across technical and business audiences

• Experience in insurance, fintech, or other regulated financial services industries.
• Familiarity with insurance concepts (underwriting, claims, actuarial workflows) or willingness to learn them deeply.
• Experience with enterprise change management or internal consulting.
• Contributions to open-source AI/ML projects or an active public portfolio of AI work.

You won't be buried in a platform team backlog. You'll sit with the business, find the highest-impact problems, and ship solutions that people use the same week. You'll have direct access to leadership, a mandate to move fast, and the autonomy to choose your own tools and approach. If you've been waiting for a role where you can prove what AI can actually do inside a real company — this is it.