Assistant Telecom Product Manager Jobs in Oregon

Platform and Agentic Product Strategy

• Own the strategy and roadmap for Conduct's agentic and platform capabilities: the API, MCP, and headless workflow surfaces that serve both human users and AI agents on a unified workflow layer and audit trail.

• Define the API surface as product: alert queues, review actions, reason-code taxonomies, workflow configuration, and the programmatic contracts that agents call. These are product decisions, not engineering ones.

• Build the extensibility model: how sophisticated customers and external or agentic systems build on the platform, including developer-facing documentation and the packaging that frames what is a subscription tier, what is usage-based, and what justifies a premium price point.

• Partner with the AI/ML product team on the boundary between the intelligence layer and the workflow layer that agents call. Keep the workflow contract clean so agents call the Conduct workflow layer while the intelligence layer powers it from beneath.

Non-Functional Requirements and Platform Readiness

• Own non-functional requirements as first-class product requirements: scale, performance, reliability, and the security posture that Tier 1 financial institutions require in diligence. Treat security, telemetry, and reliability as product surfaces.

• Translate the diligence and regulatory-examination bar of the world's largest banks into a defensible non-functional roadmap. In a regulated compliance product, a gap in any of these carries real risk.

Agentic Workflows

• Define product requirements for agentic workflows such as review, analyst assist, auto-sampling, and automations, operating on the same behavioral data asset and audit trail as human users.

• Ensure every agent's action is captured, explainable, and defensible to the same standard as an analyst decision, so the audit trail holds up to regulatory examination.

Cross-Functional Leadership

• Partner with Engineering on capacity allocation, release readiness, and operational discipline. You bring specifications complete enough for engineering to build without coming back for clarification.

• Partner with AI/ML, Data Science, Professional Services, and Customer Experience to translate customer pain into defensible priorities. Show up where customers are, not just where internal stakeholders are.

• Maintain a clear view of the competitive landscape and develop differentiated positioning grounded in product reality.

Technical Leadership and Influence

• Set the standard for platform and API/MCP product craft on the product team: problem framing, evidence-based prioritization, and outcome measurement. You raise the bar through your own work and through influence, not through direct reports.

• Mentor product managers on platform and agentic thinking. This is a dotted-line, lead-through-influence role, not a people-management one.

• 10+ years of product management experience, with a track record of shipping product at enterprise scale.
• Demonstrated API and platform product ownership: you have defined and owned developer-facing API surfaces or extensibility layers as product decisions and written the specs to prove it.
• Demonstrated non-functional requirements ownership: you have shipped products where scale, performance, reliability, or security were product requirements you owned, not issues you delegated to engineering.
• Experience building for both human and programmatic or agentic consumers, or a strong adjacent track record. Familiarity with agent frameworks or MCP-style surfaces is a plus.
• Experience with enterprise SaaS products in regulated industries. You understand what it means to ship software where wrong answers create legal or regulatory exposure.
• A track record of leading through technical authority and influence without formal reports. You have set direction and standards that others followed because of the quality of your work, not your title.
• Strong written communication. You write product specs that engineering can build from and strategy documents that executives can act on. These are different documents and you know the difference.
• Experience working in a cross-functional model with Engineering, Design, and Data Science as genuine peers, not as service organizations.

• Prior experience in financial services, compliance, legal technology, or another domain where AI explainability and auditability are not optional.
• Experience commercializing AI or ML capabilities: translating model performance into product value, and product value into pricing and packaging decisions.
• Experience managing products with both a UI surface and a developer-facing surface simultaneously. The two require different decision frameworks, and you have operated in both.
• Experience with agent frameworks, MCP, or bring-your-own-model style extensibility as a product concern.