Head of Applied AI (Innovation Office)

Quility is a modern Insurtech company transforming how life insurance and financial wellness solutions are designed, delivered, and experienced. By blending advanced technology, data-driven insights, and a human-first approach, we empower agents and partners to offer streamlined, fully digital insurance experiences at scale. With thousands of independent agents nationwide and a growing suite of proprietary platforms and products, we are redefining the future of insurance distribution. Our corporate team drives innovation across every touchpoint, enabling families across America to access the protection and peace of mind they deserve. At Quility, we’re not just keeping up with industry change, we’re leading it. 

Hands-on AI MVP builder. Executive air cover. Real budget.  
 
We're founding an AI-centric Innovation Office inside an established, well-capitalized Insurtech company and we need a technical leader who builds and ships (not a strategist who creates slide decks). The mandate is razor-sharp: take real business problems, quickly build working MVPs using LLMs and AI-native tooling (Cursor, Claude, Codex), iterate to determine whether they move the needle, and hand validated wins to our core Product team. 

If you've shipped things that worked, killed things that didn't, and want the space to do both at speed with minimal red tape and business support, keep reading.

---

THE SETUP 

The Innovation Office: The Innovation Office is a purpose-built execution unit inside Quility's enterprise structure. We exist to do what the Product team doesn’t: move fast on unvalidated ideas without touching the core platform. We're R&D. We build internal tools or time-boxed, hypothesis-driven prototypes, test unit economics in the real world, and hand validated winners to Product as de-risked business cases. 

Your Team: You will directly manage two data scientists, people who can build models, run analyses, and write SQL, but who don't ship applications.  

Your Mandate: You are the technical engine and product co-owner. Partnering with a business lead, you work within the full cycle, from evaluating whether an idea is worth building, to getting on calls with agents to understand where friction lives, to shipping the prototype, to measuring whether it worked. 

The Governance: Direction is set in close partnership with the business lead and the Chief Transformation Officer. Once aligned, you move (a lean monthly Steerco review is the full extent of the formal overhead). There is very limited sprint planning, ticket queues, or SDLC process standing between an idea and a working prototype (unless you and the business lead partner to put them there). 

The Honest Part: Our data infrastructure is real-world messy. Some of your early work will involve extracting signal from imperfect inputs. However, the Innovation Office will have a guaranteed SLA with core Data Engineering to build secure pipelines and unblock your access.

---

WHAT YOU'LL BE WORKING ON 

The problems are real and the stakes are commercial. Here's a sample of the territory: 

• An agent onboarding workflow that takes days and involves too many manual handoffs. What if it took hours 

• AI-assisted new agent training, aimed to get agents productive faster, keep them engaged, and reduce time to value. 

• Agents close some calls and lose others for reasons that are rarely documented. What if an AI layer could identify the patterns and turn them into a coaching tool to actually move close rates? 

These are illustrative, not exhaustive. The backlog is live and you'll help shape it.

---

WHAT YOU'LL DO 

Build and ship. You are the technical lead. You personally write, deploy, and iterate working software, not specs for others to build. You are practiced in using AI-native tooling (Cursor, Claude, Codex, Copilot) as a force multiplier, and you set the technical standard for your contract resource. You review their output at code depth, provide precise feedback, and translate ambiguous business hypotheses into granular, executable engineering prompts they can act on. 

Integrate data science. Your data scientists wield statistics, ML, and SQL. They help with data ingestion. You're the connective tissue that builds the scaffolding that lets their models plug into real products, so their output ships instead of sitting in an unused dashboard. While software prototypes are the primary output, some MVPs may be analytical or BI-oriented, so you should be comfortable working across both modes. 

Partner on product. You partner with the business lead on the end-to-end user feedback loop. You help conduct direct discovery interviews with opt-in agents and internal SMEs to validate whether a prototype is actually solving core friction. You help maintain the backlog, protect it from scope creep, and contribute to the team decision when a prototype isn't generating signal worth chasing. 

Evaluate the opportunity. Before a project consumes capacity, you work with the business lead to rough out its financial impact: OPEX reduction, close rate improvement, projected headcount avoidance, etc. at a level of precision that makes prioritization defensible. You help screen the backlog so the right bets get resourced. 

Develop the team. You manage two data scientists and are accountable for their output and growth. That means keeping them unblocked, pointing their skills at problems worth solving, and building their capacity to contribute to live prototypes, not just models. 

--- 

SUCCESS METRICS 

Success is measured in validated decisions, business cases that moved forward with confidence, ideas that were correctly killed before consuming real resources, and real-world impact on OPEX and revenue.

---

WHAT WE'RE LOOKING FOR 

We’re looking for a senior practicioner, someone with enough scar tissue to know what’s worth building and enough craft to build it. We want to see what you’ve personally shipped that real users touched: a live URL, a portfolio, a GitHub repo, or a product you can demo. "I contributed to a team that built X" does not count. To apply, you MUST provide a link to your work. Ideally, you will have multiple examples. 
 

Strong signals: 

• You've founded or been a founding engineer at an early-stage company 

• You have a portfolio of apps developed with AI assistance. 

• You've sourced, onboarded, and directed contract technical resources (at a technical level) 

• You've operated inside a corporate innovation, venture studio, or embedded startup context 

• Experience in insurance, fintech, or high-volume sales or distribution environments 

• Bonus: Experience with/knowledge of data science 

--- 

WHAT THIS IS NOT / WHAT WE PROTECT YOU FROM 

This role is not: 

• A "lead the team that builds" role. The team is lean. You build. 

• A research or advisory role. Your output is working software and validated decisions, not slide decks. 

---

THE OFFER

On-Target Earnings: $230,000 ($200,000 base salary + 15% annual corporate bonus target). Final compensation will be commensurate with experience, skills, and overall qualifications.

Benefits: Medical, Dental, Vision, 401(k) match, and much more!

Location: Fully remote. We care about what you ship, not where you ship it from.

This is a rare configuration: executive air cover, a dedicated sandbox, real budget, and explicit permission to move fast and kill what doesn’t work. For the right operator, this is an opportunity to build a defining track record in applied AI transformation and the kind of portfolio that travels.

---

THE COMPANY

Quility is an insurance carrier-backed Insurtech at the intersection of large-scale insurance distribution and modern technology. We operate one of the country's largest independent agent networks, supported by a proprietary lead generation marketplace and a growing B2B software platform. We are profitable, well-capitalized, and in the middle of a deliberate enterprise modernization, which is why we're founding this Innovation Office.