The Role

We're looking for a Product Manager to own one product pillar and one platform:

Program Intelligence is the pillar behind Ava, our employer-facing AI agent. Ava isn't a dashboard or a reporting tool. It's an agentic intelligence that monitors a customer's entire self-funded benefits program, proactively surfaces insights, and lets benefits leaders ask any question in natural language and get analyst-grade answers in seconds. It coordinates specialized sub-agents across claims analysis, vendor performance, cost modeling, and more. You'll shape how Ava gets smarter, what it proactively surfaces, and how it helps benefits leaders go from reactive to strategic.

Core AI is the applied AI platform that powers everything else at Avante. This team builds the agentic infrastructure the rest of the company relies on: retrieval systems, agent orchestration, model evaluation, prompt architecture. You'll help define what gets built, how it's prioritized, and how the platform evolves as our product surface grows.

This combination means you need real technical fluency. You don't need to write production code, but you do need to understand how agentic systems work, how data flows through a platform, and how to have productive conversations with engineers about architecture tradeoffs and system design.

Avante is high-growth and the product landscape is evolving quickly. Ownership areas will shift and expand as we scale. The right person for this role is energized by that, not anxious about it.

This role is a fit for someone 3–4 years into their product career who has shipped real product, is deeply curious about how AI is changing what PMs can do, and wants to operate at a pace where weeks feel like months.

What You'll Do

Own a product pillar and a platform with real technical depth. Define roadmap and priorities for Program Intelligence and Core AI. Make tradeoff decisions across agentic intelligence for employers and the shared AI infrastructure underneath it.

Collaborate across the product team. You'll work alongside another PM who owns different product areas. Avante's agents and platform capabilities are deeply interconnected, so tight collaboration across pillars is essential. You'll need to coordinate on shared infrastructure decisions, align on how changes in one area affect the other, and collectively maintain a coherent product vision as the platform grows.

Shape how an AI agent thinks and acts. Ava isn't static software. It reasons, coordinates sub-agents, and produces analysis on demand. You'll define what it proactively surfaces, how it handles ambiguity, and how its intelligence compounds over time as more data sources connect.

Translate AI capabilities into product decisions. Work with engineering to shape how models, retrieval, agent orchestration, and structured data come together in production. Understand enough about these systems to have opinions, not just questions.

Use AI tools as a core part of how you work. We expect our PM to use Claude Code (and tools like it) daily: to prototype ideas, self-serve technical questions, build internal tools, and create agents that accelerate their own workflow. If you've been following how folks on Lenny's Podcast talk about the AI-augmented PM, that's the profile we're looking for. Not someone who's read about it. Someone who's doing it.

Drive outcomes through data. Own metrics across activation, engagement, and expansion for your product areas. Use claims data, usage patterns, and customer feedback to inform what you build and how you measure success.

Define quality for AI systems. Partner with engineering to establish evaluation approaches for agent behavior, output reliability, and response quality. Avante has zero hallucination tolerance. Build the feedback loops that keep it that way.

Stay close to customers. Talk to benefits leaders and HR teams regularly. Develop a clear understanding of where the product is delivering value and where it falls short. Bring that signal back into prioritization with urgency.

Adapt as we grow. Product ownership at Avante will evolve as the company scales. You should expect your scope to expand into new product areas over time, and you should welcome that.

What We're Looking For

• 3–4 years of product management experience, ideally in B2B SaaS

• Experience working on technically complex products (AI-powered, data-intensive, or platform/infrastructure)

• Enough technical fluency to engage meaningfully with engineers on system design, data architecture, and AI/ML concepts

• Active, hands-on use of AI coding and prototyping tools (Claude Code, Cursor, or similar) in your product work, not just familiarity with the category

• A data-driven approach to product decisions, with experience defining metrics and analyzing performance

• Comfort with ambiguity and the ability to create structure where little exists

• Strong communication across technical and non-technical stakeholders

Nice to Have

• Experience with agentic systems, LLM-powered products, or AI infrastructure in production

• Familiarity with benefits, healthcare, or HR tech

• Early-stage startup experience

• Experience working on products that serve both enterprise buyers and end users

How We Work

Our four values aren't aspirational. They translate into concrete operating tenets that shape how we make decisions every day.

Beat Yesterday. We re-evaluate our own toolkit every quarter, because the workflows that made you effective three months ago may already be outdated. We act on 70% of the information rather than waiting for certainty. We timebox, execute, and iterate, getting work in front of real people quickly instead of polishing in isolation. And we own our output regardless of how we produced it. AI can get you 80% of the way there. Everything that goes out with your name on it is your responsibility to review, refine, and stand behind.

Embrace Type 2 Fun. We take on hard problems and find meaning in the work, even when it's uncomfortable. We assume good intent and follow up directly rather than venting in side channels. We celebrate wins loudly and specifically, naming the actual behavior so the whole team learns what great looks like. We are on by default, because we owe it to each other and to our customers to be available beyond what a regular corporate job would demand. And we do unscalable things today that build scalable advantages tomorrow: every white-glove implementation, every hand-built QBR deck, every late-night RFP turnaround earns us the right to scale later.

Stay Hungry, Stay Curious. We expect everyone to be the expert on AI in their function before anyone asks them to be. The landscape changes weekly. When you learn something, teach it. Learn enough about adjacent functions to ask good questions. Ask the question you think is too basic, because in complex domains like benefits, the cost of a wrong assumption can be a lost account. And remember: curiosity without urgency is a hobby. Learning has to translate into action on a timeline that matches the opportunity.

Act Like an Owner. We say the uncomfortable thing early, raising missed commitments or quality gaps directly with the person within 48 hours. We surface problems when they're small, not the week they become a crisis. Customer-facing work gets priority, always. And we close the loop every time, because over-communication is a feature at our stage, not a bug.

130000 - 150000 USD a year