{"id":37349,"url":"https://alion.io/job/exactera-principal-product-manager-agentic-platform","title":"Principal Product Manager (Agentic Platform)","company":{"id":8368,"name":"Exactera","domain":"exactera.com","url":"https://alion.io/company/exactera","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Product","role_family":"Product","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":139000,"max_usd":272000,"period":"year","method":"global_role_seniority_cell","sample_n":1427},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false}],"status":"live","first_seen_at":"2026-06-22T16:29:13Z","employer_posted_date":"2026-06-22","last_verified_at":"2026-10-24T06:45:24Z","board_verified":true,"closed_at":null,"days_open":123,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":123},"description":"Exactera has offices inNew York City, Tarrytown NY, San Diego, CA, London, and Argentina. \nAbou the role\nExactera helps large multinationals handle complex tax work: transfer pricing, R&D tax credits, indirect tax, and audit defense. We are moving from a software-and-services model to an AI-native platform that does the work itself, with tax practitioners applying judgment where defensibility requires it.\nThis role owns the product direction for the agentic platform behind that shift: the system that enables AI agents and practitioner tools to run tax analysis on trusted, current data. The data foundation (a lakehouse, external sources, and the contracts that keep them reliable) is the substrate. The product is what agents and practitioners can do with it.\nYou work directly with the Principal AI Engineer, who owns the AI/ML architecture, and the Principal Data Engineer, who owns the data tier. You own what the platform does, in what order, and why. Because you define how the company’s practitioners and agents use AI, you have to work deeply in these tools yourself.\nExactera is growth-stage, so the role comes with equity and the room to set the platform’s direction yourself.\nWhat you'll do\nThe six outcomes that define success in the first 18 months.\nO1. Own the product strategy and roadmap for the platform.\nYou own what the platform is for and what it builds next. The roadmap ties to practitioner outcomes rather than feature counts. When priorities compete across engineering, product, and the practice teams, you decide and keep everyone working from the same plan.\nO2. Define what compliance-grade means for this platform.\nTax work has to be defensible. You set the product requirements that make the platform’s output trustworthy: where results must be deterministic, what guardrails constrain agent behavior, how tool access is scoped, and what has to be auditable. You decide where human judgment stays in the loop. This is the bar that regulated tax work requires and general AI tooling does not clear.\nO3. Own the agentic access surface.\nThe platform’s main product is the surface AI agents and practitioner tools use to reach data and act on it. You own that surface: the interface, the contracts behind it, and the limits on what agents can do. How this works decides how the whole platform gets used.\nO4. Treat the data foundation as a product.\nThe data foundation is what the rest depends on, so you manage it as a product. With the Principal Data Engineer, you set the contracts between data producers and consumers: schema, quality, and freshness as commitments practitioners can rely on.\nO5. Make external data a platform capability.\nThe platform is only useful if it reflects what happens outside it: regulatory changes, SEC filings, financial data, third-party sources. You decide which sources matter and how they show up in the product, weighed against their cost. Each is a coverage and value decision.\nO6. Measure success by practitioner outcomes.\nYou measure success by what practitioners can do with the platform: faster, more accurate work with less of it done by hand. A pipeline in production that does not change a practitioner’s day has not succeeded.\nWhat we're looking for\nRequired\n10+ years in product management, with significant time on technical platform, data, or ML products. You have owned a platform or major product area at Principal-level scope and driven it across teams without positional authority.\nAble to set product direction across a modern data platform. You understand Lakehouse and medallion patterns, data contracts, quality, and lineage well enough to decide direction and hold credibility with platform engineers, without needing to build it yourself.\nTrack record owning AI or ML platform work from an ambiguous problem through to production.\nStrong understanding of agentic AI systems and the data access they require: retrieval, tool calling, MCP or equivalent. You can reason about how agents reach data and what should constrain them.\nExperience with AI systems where correctness and defensibility matter. You have worked on evaluation, guardrails, or human-in-the-loop design, and you understand why a regulated workflow needs more than a capable model.\nYou decide what success means for a platform and measure it by practitioner results.\nYou communicate clearly across engineering, product, and the practice teams. You hold a high bar without leaning on process, and you work well in ambiguity.\nYou use AI tools as part of how you work day to day, and you share what you learn with the people around you.\nPreferred\nExperience in tax, financial reporting, regulatory compliance, or another regulated, data-intensive professional services domain.\nBuilt or governed data products, internal or external, including external-data sourcing and licensing and the trade-offs between coverage, cost, and reliability.\nHands-on familiarity with Databricks, Delta Lake, or a comparable lakehouse platform in production.\nBackground in tech-enabled services or a SaaS-to-services transition like the one Exactera is making.\nBuilt a platform or major product area from early stage.\nWhat We Offer: (The following only applies to US-based positions)\nA collaborative team culture with opportunities for career development. \n\nAmple opportunities to be recognized, build valuable skills, and grow your career. \n\nGenerous vacation policy, including paid parental leave. \n\nComprehensive health plans with FSA and HSA options. \n\n401(k) retirement plan. \n\nLife and disability insurance coverage. \n\nSupplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. \n\nAbout Us:\nAt Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. With over $100 million in funding from Savant Venture Fund and Insight Partners, we are poised for growth. 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