Senior Product Manager, Data Platform – Intelligence

Jobtailor; California (MO); On-site; USD 140,000 - 190,000; Full time

Job summary

Invoca is seeking a data platform and intelligence products leader to own the end‑to‑end roadmap for our data platform and AI‑driven offerings.

You will define and launch signals, scores, and insights that create measurable value for internal teams and paying customers, and structure how context is delivered to AI agents across voice, SMS, and web.

Qualifications

• 5+ years in product management with data platforms, AI infra, analytics or intelligence products.
• Technical fluency to partner with data engineers and AI teams on architecture and schema evolution.
• Experience with data lake/warehouse platforms at scale (Snowflake/BigQuery/Redshift).
• Proven track record building intelligence products used by internal teams and customers.
• Experience in enterprise SaaS with data governance and multi-tenant considerations.

Responsibilities

• Own end-to-end roadmap for data platform and intelligence products.
• Define and launch signals, scores, and insights that deliver measurable value.
• Structure, stage, and deliver context to AI agents across voice, SMS, and web.
• Own intelligence and data products used to build customer experiences atop Invoca data.
• Drive cross-team execution, manage dependencies, and unblock teams.
• Build data apps and agents on the data lake powering use cases across the business.
• Partner with data engineers and ML teams to balance freshness, coverage, latency, and cost.
• Define success metrics and measure adoption, coverage, and quality signals.
• Evaluate build vs. buy for data infra and guide vendor integrations.
• Stay current on retrieval and grounding patterns for pragmatic product decisions.

Skills

Product management

Data platforms

AI infrastructure

Cross-functional leadership

Data lake / warehouse

Tools

Snowflake

BigQuery

Redshift

Job description

Responsibilities

• Own the end-to-end roadmap for Invoca's data platform and intelligence products
• Define and launch intelligence products – signals, scores, and insights – that create measurable value for both internal teams and paying customers
• Define how context is structured, staged, and delivered to AI agents across voice, SMS, and web – ensuring every interaction is grounded in the right data at the right time
• Own the intelligence and data products that other teams and customers use to build unique experiences on top of Invoca data
• Drive cross-team execution across teams working on the agentic platform, conversational AI products on voice and SMS, signals, and insights – managing dependencies, driving prioritization, and keeping work unblocked
• Build data applications and agents on our data lake that power product use cases across the business – from agent performance measurement to customer outcome analytics
• Partner with data engineers and ML teams to make principled tradeoffs across data freshness, coverage, latency, and cost
• Define success metrics for data products and continuously measure impact through adoption, coverage, agent performance, and quality signals
• Evaluate build vs. buy decisions for data infrastructure and guide vendor integrations behind stable, well-defined contracts
• Stay current on advancements in retrieval, grounding, and context injection patterns – translating signal into pragmatic product decisions

Requirements

• 5+ years of product management experience, with meaningful time in data platforms, AI infrastructure, analytics products, or intelligence products
• Technical fluency sufficient to partner closely with data engineers and AI teams – comfortable in architecture discussions, familiar with data modeling, pipeline design, and schema evolution
• Hands‑on experience working with data lake or data warehouse platforms (e.g., Snowflake, BigQuery, Redshift, or similar) – you understand how data products are built, governed, and consumed at scale
• Experience building intelligence products – signals, scores, insights, or recommendations – that both internal teams and external customers depended on
• Familiarity with evaluation approaches for data‑driven AI systems – you have a point of view on how to know whether a context or signal pipeline is actually working
• Experience in enterprise SaaS or compliance‑heavy domains where data governance, auditability, and multi‑tenant isolation are core design constraints, not afterthoughts
• Strong execution ownership – you drive prioritization, own cross‑team dependencies, and unblock your team without waiting to be asked
• Ability to move fast with imperfect information – this is a fast‑moving AI environment; the bar is calibrated judgment, not perfect context
• Clear communicator who can translate complex data and AI concepts for both engineering and business stakeholders without losing precision on either side
• Track record of making principled tradeoffs across data quality, latency, cost, and reliability in complex systems.