AI Deployment Lead

Strada•New York, NY

20h•Onsite

About The Position

Strada is building the agentic workforce for insurance operations. Our platform deploys expert AI agents across calls, texts, emails, and chat – running core front-office workflows from policy servicing to claims intake. With a singular focus on insurance, Strada offers domain expertise and product depth that generic AI platforms can't match. Backed by Y Combinator and top-tier investors, Strada already automates millions of customer interactions for leading insurers, MGAs, and wholesalers representing $10B+ in annual premiums. We are embedded in production systems at sophisticated organizations – not running pilots, but driving real operations. It is now certain that AI in insurance operations will become a multi-billion dollar category. The question is not if, but who wins. We are already ahead in deploying AI at scale and intend to define that category. If you want to operate at the intersection of AI, enterprise software, and real-world execution – and be part of a company that is winning – let’s talk. Why Insurance? Insurance is a $300B+ industry that quietly powers the global economy – enabling businesses to operate, families to recover from disasters, and entire sectors to manage risk. Yet its core operations remain largely unchanged. Many critical workflows still rely on manual processes, phone calls, and fragmented legacy systems. That is now changing. AI is beginning to automate these workflows end-to-end – not as a layer of assistance, but as the system of execution. This shift will redefine how insurance operates and unlock billions in efficiency gains. Strada is building that infrastructure. The Role We’re looking for an AI Deployment Lead to own how Strada’s AI agents go live and scale within enterprise insurance organizations. You will sit at the intersection of client operations, AI capabilities, and product execution – acting as the primary interface between our customers and our product. This is not a traditional consulting role. You won’t be delivering recommendations and stepping away. You will own outcomes end-to-end: from understanding the problem, to deploying the solution, to ensuring it works in production. You will: Work directly with senior client stakeholders (COOs, CIOs, Heads of Operations) Translate complex, messy workflows into deployable AI systems Drive decisions under constraint and align multiple stakeholders Be accountable for real-world performance, not just delivery This role is particularly well-suited to candidates from top consulting backgrounds who want to move from advising to owning outcomes. You will work directly with the founding team, including the CTO, and operate with a high degree of autonomy and responsibility from day one. What you'll get done in the first week Shadow live deployments and review real AI agent conversations across thousands of workflows Get deep into the product – understand how agents are configured, deployed, and monitored Identify where you can have immediate impact on active client engagements What you'll do in your first 30 days Own your first deployment end-to-end – from scoping to go-live Run structured sessions with client teams to map workflows and define success Build a strong understanding of the operational realities of insurance systems What you'll do in your first 90 days Lead multiple deployments concurrently across enterprise clients Navigate tradeoffs across timelines, engineering capacity, and client expectations Become a trusted counterpart to senior stakeholders on how to scale AI in their operations Surface patterns from deployments that shape product direction and company strategy

Requirements

4–7 years of experience in management consulting, product, or a high-performance client-facing role
Proven ability to own complex, multi-stakeholder problems end-to-end
Strong structured thinking – you break ambiguity into clear decisions and drive alignment
Excellent communication skills – you can run a room with senior stakeholders (COOs, CIOs, Heads of Operations) and drive decisions forward
High ownership mindset – you take responsibility for outcomes, not just recommendations
Comfort with technical systems – you don’t need to code, but you understand how systems behave and how to work with engineers