Lead / Senior Product Manager Analytics, Evals & Conversational BI (Agentic at Netomi

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

12 Apr, 26

Salary

0.0

Posted On

12 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, Data Science, Analytics, Data Modeling, Telemetry, ETL, ELT, A/B Testing, Governance, UX Design, Information Architecture, Operational Reporting, Business Reporting, Conversational BI, LLM Evaluation, Observability

Industry

Software Development

Description

About the Company: Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us! About the Role Netomi is hiring a Lead/Senior Product Manager to own the Analytics, Reporting, and Conversational BI product surfaces in Agentic Studio—the measurement and trust layer that helps enterprises build, operate, and continuously improve agentic customer experiences across chat, mobile, email, messaging, and voice/IVR. In mission‑critical environments (airlines, retail, banking, gaming), analytics is not a “dashboard”; it’s the control plane for reliability, governance, and outcomes. You will lead the productization of end-to-end analytics including real-time operational monitoring, historical reporting, LLM quality/evaluation (autoevals), observability for tool calling and workflows, and Conversational BI (natural language exploration over a governed metrics model). This role requires deep domain fluency in data science, data preparation, analytics systems, and the realities of LLM-driven systems (probabilistic outputs, evaluation, safety/guardrails, and runtime tracing)—combined with strong product craft, design sense, and delivery execution. This is an opportunity to lead with data at the frontier: partnering with internal Data Science and Engineering teams while collaborating with frontier model and cloud ecosystem partners to deliver best-in-class analytics and governance for enterprise agentic AI. \n Responsibilities Define and execute the Analytics/Evals/Governance roadmap with clear sequencing (MVP → v1 → v2) and measurable adoption targets. Partner deeply with Data Science to productize evaluation methodology (what we score, how we calibrate, how we prevent “gaming,” how we track drift). Partner with Engineering and Observability teams to standardize telemetry (tool spans, workflow transitions, model calls, cost/latency metrics) and make it usable in product. Drive a cohesive Agentic Studio UX across Build / Operate / Improve workflows: dashboards, drill-downs, investigation flows, alerts, and remediation actions. Establish objective success metrics and instrument them end-to-end (data correctness, timeliness, reliability, and customer impact). Work with Delivery/CS and enterprise partners to ensure analytics is usable for real operational processes: incident response, change management, governance reviews, and quarterly business reviews. Requirements Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative/technical field (Master’s a plus). 6–10+ years of experience across Product Management and/or Data Science/Analytics leadership, including shipping analytics products to enterprise users. Demonstrated depth in: data modeling, telemetry/event schemas, ETL/ELT concepts, and analytics correctness. Building operational + business reporting (real-time monitoring and historical analytics). Experimentation and measurement design (A/B testing concepts, uplift measurement, cohorting). Strong hands-on experience applied to AI/LLM or data science platforms, including at least several of: LLM evaluation methods (automated scoring, multi-turn evaluation, calibration). Observability for probabilistic systems (quality + latency + cost). Tool calling / workflow execution analytics and failure taxonomy. Governance measurement (policy outcomes, escalation triggers, compliance reporting). Strong product craft: UX and information architecture instincts, ability to design operator workflows, and capability packaging that scales across customers. Preferred Experience building analytics for multi-tenant SaaS and regulated customers (auditability, RBAC, retention controls, privacy-by-design). Familiarity with cloud analytics stacks and enterprise BI integration patterns. Experience partnering with major cloud and frontier AI vendors (model providers, observability stacks, data platforms) to ship joint capabilities. Experience with contact center / CX metrics (containment, resolution, AHT, CSAT, handoff performance) and multi-channel operations (voice + digital). \n Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

Responsibilities

Define and execute the Analytics/Evals/Governance roadmap while partnering with Data Science and Engineering teams. Ensure analytics is usable for operational processes and establish objective success metrics.