Technical Product Manager

Key Responsibilities

• Develop and clearly articulate the product strategy, aligning with company objectives and the evolving market landscape.
• Own products and outcomes end to end, from initial concept through deployment and continuous enhancement, ensuring delivery on time, within scope, and beyond expectations.
• Bridge complex technical solutions and tangible business value, making informed prioritization decisions and smart trade-offs.
• Data Platform & Pipeline Design and continuously optimize the platforms through which licensors provide and transfer large-scale data to Troveo, from multimodal content to enterprise workflow data.
• Own the end-to-end ingestion experience, from onboarding workflows to file-transfer reliability, making it seamless for partners of all technical sophistication levels.
• Partner closely with engineers to build and refine a cost-effective, high-throughput data pipeline covering profiling, deduplication, transcoding, annotation, and downstream delivery.
• Help design processing pipelines and logic tailored to diverse data types, including video files, structured metadata, and other custom formats submitted by licensors.
• Identify bottlenecks, propose improvements, and drive execution across pipeline stages.
• Own analytics and data-driven feature improvement, using metrics to identify opportunities, prioritize work, and measure impact.
• Dive deep into the data to address operational data issues, maintaining data quality and consistency across the pipeline.
• Partner across teams to meet client delivery needs, including data reconciliation across systems.

Job Requirements

• 5+ years of product management or a similar role in a technically demanding field.
• Maturity and strong judgment across both business and technology, with a demonstrated ability to influence and lead.
• Comfortable in having conversations with technical stakeholders, with the ability to translate complex concepts for any audience.
• Strong command of SQL and data analytics, with the ability to dive into the data to answer your own questions and validate hypotheses.
• Strong analytical thinking, structured problem-solving, and data-driven decision-making.
• Ability to go from problem to spec to shipped feature, working efficiently with engineers.
• A hands-on, experimental approach to AI, continually testing and adopting new capabilities as they emerge.

Preferred / Nice-to-Have

• Familiarity with video processing workflows (e.g. transcoding, format standards, metadata handling).
• Experience in content licensing, media tech, or AI training data environments.
• Experience working with tools in the AWS ecosystem (e.g. S3, ECS, Lambda, Glacier, etc.).
• Comfortable reading or writing Python and other programming languages.
• Ability to build lightweight internal tools and proofs-of-concept using the latest AI tools and technologies.