• Customer Discovery. Immerse yourself in customer workflows, constraints, motivations, and pains. Capture revealed preferences and weigh them against stated preferences and internal vision. Use this to maintain strong intuitions and data-backed positions on where the product should go. • Roadmap Alignment. Synthesize customer learnings, the existing roadmap, sales requests, and engineering priorities into a sequenced plan that different teams can execute against. • Outcomes Ownership. Own outcomes from vaguely identified needs to solutions with real-world impact. Define what to build and why. Identify, surface, and reconcile tradeoffs. Push through cross-functional blockers. Be the CEO of whatever initiative you’re involved with. • Measurable Outputs. Introduce metrics wherever helpful. Own tracking and iterating based on them. • Sales Enablement. Review personalized sales collaterals. Join prospective calls. Work closely with BD to help close deals. • Institutional-Grade Product Readiness. Bake real institutional requirements — control, permissioning, auditability, performance guarantees, operational clarity, risk, SLAs, procurement — into product decisions from day one. • Cross-Functional Facilitation. Find blockers throughout tech, sales, and marketing and proactively help unblock them.

• Own the vision and roadmap for Employee Training product • Integrate AI capabilities into product • Accelerate team's discovery and delivery cycles with AI • Define clear, prioritized work from ambiguous problems • Collaborate across Engineering, Design, Data, and Marketing

Role Description This is a broad Senior PM role on the quality, trust, and communication side of service delivery — setting the right expectations on both sides, steering Pros to deliver great work, resolving conflicting interests fairly, and making our AI-powered support genuinely good. You'll work on live, high-scale systems with a mandate to make them better. Service delivery is a big area with more than one PM in it. You'll work alongside them; your center of gravity is the trust between both sides of the marketplace. What makes this role different: - It's a real area of impact, not a single feature. You'll shape strategy, policy, and the systems behind a whole slice of the post-booking experience — not optimize one screen. - It's inherently two-sided. You work for customers and Pros at once, and you're often the one arbitrating between them. Pleasing one side at the other's expense is failure. - AI is a core tool, not a side project. Support and outreach already run on AI. You'll push how far that goes — and build the evals that prove it's good before we trust it with more. Problems to Solve: - Getting expectations right before the work ever starts. Most service failures aren't bad work — they're mismatched expectations. - Arbitrating genuinely competing interests. A customer wants a date the Pro can't commit to. The grass is long enough to need a different price tier than booked. - Making AI trustworthy enough to do more — which means evals. You'll own the eval systems that define what "good" means for an open-ended conversation. - Messaging that connects both sides — and quietly protects the marketplace. What Success Looks Like (Year 1): - Expectations match on both sides: Pros know exactly what each job requires, customers get what they expected. - Competing interests resolve faster and more fairly: A clearer resolution model with measurable consistency. - AI is provably good, and does more: An eval suite gates AI changes so no quality regression ships unseen. - Messaging connects and protects: Measurable improvement in messaging reliability and engagement. Qualifications - AI-native: You use AI daily in your own work and have real intuition for how to measure whether an AI experience is actually good. - Comfortable making two-sided calls: You can hold both the customer's and the Pro's interest in your head at once. - You design for the right outcome up front: You're not satisfied grading work after the fact. - A marketplace systems thinker: You see service delivery as a system of incentives, policies, and feedback loops. - Data-informed: You live in the numbers that matter here — CSAT, resolution rate, eval scores, churn, deflection. - Technically fluent: You partner with engineers on how AI and messaging systems work. Requirements - This Role Is NOT a support PM role. - The internal-AI role. - A greenfield 0→1 role. - A single-audience role. Benefits - Base salary: $140,000 - $170,000 - Equity: The systems you'll work on touch every customer and Pro. - Healthcare: Medical, dental, and vision. - Fully remote: Work from anywhere in the US. - Flexible PTO: We Focus On Results.

Role Description We’re building AI that makes great advertisers even better. You’ll build the tools that make it happen. Our Creative Strategy team is in the middle of building an AI-powered infrastructure that changes how strategists work — from how they plan campaigns to how they write briefs to how they evaluate creative. We need someone to build it. What you’ll actually be doing: - Building and shipping AI tools — roadmap generators, brief scorers, hook writers, sprint planners, competitive intelligence tools. Real tools, used daily, with real usage metrics. - Owning the data pipeline — turning raw performance data, consumer reviews, and competitive intel into structured inputs that feed every downstream tool. Python scripts, API integrations, SQL queries — you’ll write and maintain all of it. - Managing the AI architecture — client-specific Claude Projects, skill files, knowledge bases. Every account should eventually have custom AI context that makes strategy work faster. - Driving adoption — a tool nobody uses is a tool that doesn’t exist. You’ll train the team, gather structured feedback, track usage, and iterate until it sticks. Qualifications - You’re a strong Python developer comfortable writing production scripts, not just prototypes. - You’ve worked with APIs (REST, JSON) and can integrate LLM APIs without hand-holding — experience with OpenAI or Anthropic is a plus. - You’re comfortable with SQL at a working level — pulling data, writing joins, debugging pipeline issues. - You can get something deployed (Vercel, Railway, or equivalent) independently. - You learn fast in new domains — you don’t need to know advertising coming in, but you need to pick it up quickly. - You ship things. You document things. You own things. Requirements - You’re not a fit if you want to experiment and prototype indefinitely without shipping. - You expect a ticket queue and explicit instructions for everything. - You’re looking for a pure engineering role with no business context. Benefits - Base: $65,000–$85,000 depending on experience. - Tool impact bonus for each qualifying tool with 5+ sustained weekly active users. - Additional bonus at 10+ weekly active users. - Targets: 2 qualifying tools in your first 6 months, 5+ by end of year one. The honest pitch This role has a steep learning curve. You’ll be picking up prompt engineering, advertising strategy vocabulary, and a proprietary methodology while simultaneously building and shipping tools the team uses every day. It’s not for everyone. But if you want to build AI infrastructure that has measurable impact on a real business — and you want to learn direct-response advertising from the inside while doing it — this is a rare opportunity to do both at once.