Technical Product Manager

Technical Product Manager

Wowza powers the world's leading live and on-demand streaming experiences.

From global events and enterprise broadcasts to AI-powered video intelligence at the edge, Wowza provides the most trusted, extensible, and developer-friendly streaming platform on the market.

As we move into the next era of streaming, we are expanding our product organization with builders who combine technical depth, analytical rigor, and a customer-first mindset.

The Role

The Technical Product Manager (TPM) translates customer insights and data analytics into actionable engineering plans that drive measurable business outcomes. This role sits at the intersection of Product, Engineering, and Customer Success, ensuring every initiative is prioritized through data, executed efficiently, and aligned with Wowza's strategic goals.

You will balance strategic roadmap definition with hands-on delivery coordination, working to remove blockers, optimize workflows, and back every decision with evidence, from product telemetry to win-loss insights. The TPM will lead initiatives that enhance visibility, accountability, and execution across the product lifecycle, ensuring Wowza's innovations reach market efficiently and deliver real customer impact.

What You'll Do

Data-Driven Roadmap & Prioritization

Use product telemetry, analytics, and customer feedback to define priorities and validate roadmap decisions.

Partner with Product and Engineering leads to ensure each initiative is justified by measurable data such as usage trends, customer outcomes, or revenue impact.

Program Execution & Delivery

Translate product strategy into clear technical milestones and delivery plans.

Track engineering progress using Agile tools (e.g., Jira, Confluence) and maintain visibility into scope, risks, and timelines.

Define and monitor KPIs (velocity, on-time delivery, quality metrics) to ensure engineering work aligns with company objectives.

Cross-Functional Alignment

Act as the bridge between Customer, Product, Engineering, Sales, and Support to maintain shared understanding of priorities and timing.

Lead communication and status reporting for internal stakeholders and executives, using data-driven updates that highlight customer and business outcomes.

Workflow Optimization

Identify bottlenecks across the delivery process and drive continuous improvement using retrospectives and metrics.

Implement scalable frameworks for estimation, risk management, and dependency tracking across multiple teams.

Customer-Centric Outcomes

Leverage winloss insights, support feedback, and field data to ensure features directly improve customer experience and market competitiveness.

Partner with Customer Success to quantify adoption, retention, and satisfaction improvements tied to product releases.

Resource Planning

Coordinate with engineering management to ensure optimal team capacity and prioritization.

Balance short-term delivery pressure with long-term product scalability and technical excellence.

What You Bring

5+ years in Technical Program or Product Management within a software or SaaS environment (streaming experience preferred).

Proven ability to use data and telemetry to drive decisions and measure results.

Experience managing Agile development lifecycles and working closely with engineering teams.

Strong analytical mindset with the ability to define KPIs, interpret trends, and make recommendations grounded in evidence.

Excellent communication skills across technical and business audiences; able to translate between product vision and engineering execution.

Technical fluency in APIs, SDKs, and modern cloud infrastructure.

Familiarity with streaming technologies such as HLS, WebRTC, RTMP or SRT.

Leadership experience driving accountability and alignment across multiple teams.

Strong Plus

Experience deploying and using on-premises streaming media platforms.

Familiarity with product analytics tools (PostHog, Pendo, GA4) for telemetry and performance tracking.

Experience with computer vision, AI, or machine learning in streaming or video analytics.

Experience with containerized or edge deployments (Docker, Kubernetes).