Technical Product Manager

The short version: Datalign Advisory has five AI-powered solutions serving the wealth management industry. We’re looking for a Principal Product Manager, IC (Technical) to own our flagship product: Halo — an AI wealth management companion that gives consumers SEC-compliant, personalized financial guidance through coordinated AI agents, and connects them with fiduciary advisors when they’re ready.

About Datalign:

Datalign Advisory is a Cambridge-based fintech building the comprehensive AI-native platform for how Americans find, evaluate, and work with financial advisors — and how advisors grow. Our platform spans five products: curated lead generation, GEOsAI geographic intelligence, RelationshipAI prospect insights, Halo consumer engagement, and a customizable agentic AI layer for advisory firms.

Most companies in this space pick one lane — they’re a matching platform, or a CRM enrichment vendor, or a scheduling tool. We’re building the integrated infrastructure layer underneath all of it, powered by a proprietary knowledge graph of 200M Americans.

We’ve served 100,000 consumers, referred $80B in assets to 13,000 advisors, won Financial Advisory Platform of the Year at the 2026 FinTech Breakthrough Awards, and recently opened our compliance-by-design agentic AI platform to advisory firms across the industry. We’re small, we move fast, and the problem space is genuinely hard.

Please note:  We are only accepting applications from candidates in the Greater Boston area, as this is a hybrid role with 4 days a week in office.

About Halo:

Halo is Datalign’s consumer-facing AI wealth management companion. Through Plaid integration and user consent, Halo connects to a consumer’s actual financial accounts and delivers personalized guidance grounded in real data.

Under the hood, Halo is powered by specialized AI agents orchestrated across multiple domains — this isn’t a chatbot bolted onto a product, it’s intelligence native to every layer of the experience. Consumers can explore their finances independently, model scenarios against their actual numbers, and connect directly with a fiduciary advisor within the platform when they’re ready.

Halo also closes the loop on the advisor side: when a consumer uses Halo between meetings, those insights and questions flow back to the advisor as briefings. The advisor doesn’t have to spend time uncovering what’s on the client’s mind — they already know when they get on the call.

You’d own Halo end-to-end. That means:

• Defining the product roadmap for Halo based on what you learn from consumers, advisors, and the data — not from a roadmap inherited from a committee. At our stage, the PM is the strategy.
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• Shaping the consumer experience from first interaction through advisor connection. You’ll decide how Halo builds trust, how it guides financial exploration, and where the human handoff to an advisor happens.
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• Working directly with engineering and data science to ship. Halo’s architecture involves multi-agent orchestration, compliance-grade infrastructure, and real-time financial data pipelines. You need to understand how these systems work well enough to make sound product tradeoffs.
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• Figuring out how to measure success in a two-sided product where the consumer experience and the advisor experience are deeply coupled. What’s good for the consumer using Halo needs to also make the advisor’s first conversation better.
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• Navigating compliance constraints as a feature, not a blocker. We’re SEC-registered. Every AI interaction in Halo carries source traceability and reasoning chains. You’ll need to think in those terms natively.
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• Thinking in platform context. Halo doesn’t exist in isolation — it sits within a broader ecosystem of Datalign products. Your decisions need to account for how Halo reinforces and is reinforced by the rest of the platform.
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• Making hard prioritization calls with limited resources. This is a seed-stage company, not a business unit inside a large org. You’ll feel the cost of every wrong bet.

What we are looking for:

• You know how to build great AI products. This is non-negotiable. You’ve shipped AI-driven products — whether that’s LLM-based applications, multi-agent systems, ML pipelines, or AI-powered consumer experiences. You understand the difference between a demo and a product, and you know what it takes to get AI into production at a quality bar users trust.
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• You use AI in your own workflows — and you can show the receipts. We want to hear specifically how you use AI tools today: to move faster, to think more clearly, to prototype, to analyze data, to draft and iterate. How does it change your pace? How does it change how you engage with engineering? A PM who builds AI products but doesn’t use AI to do their own job is missing something fundamental.
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• You’ve operated in a high-bar engineering culture. Our leadership team comes from MIT, Amazon, and Meta — we think in terms of working backwards from the customer, writing docs before writing code, and holding a high bar on technical decisions. If that operating language is native to you, you’ll ramp fast.
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• But you’re genuinely excited to apply that rigor at startup speed. The frameworks matter less than the thinking behind them. We need someone who can take the best of what they learned at scale and adapt it — ruthlessly — to a company where speed and judgment matter more than consensus.
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•  7 years in product management with at least some of that time on technical products where you needed to deeply understand the underlying systems.
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• Experience shipping in regulated or compliance-heavy environments (fintech, healthtech, govtech — the specific domain matters less than the muscle of building within constraints).
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• The ability to talk to a financial advisor who’s been in the business for 25 years and to an engineer debugging an agent orchestration issue, and be credible with both.
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• Strong written communication. We’re a small team — clear docs, concise product specs, and well-framed decisions matter more here than in a company with layers of PMs above and below you.

Nice to Have:

Experience with multi-agent systyems, agentic AI Archictecutres, or LLM-based consumer products

Familiarity with the wealth management or financial advisory industry.