Technical Product Manager QVAC

Tether Operations Limited

The goal of the Senior Technical Product Manager for the QVAC SDK is to define, guide, and scale the developer-facing product strategy for QVAC s local and distributed AI platform.

This role bridges deep software engineering understanding, developer experience design, market insight, and product execution. The QVAC SDK enables developers, enterprises, and ecosystem partners to build privacy-preserving, on-device, and peer-to-peer AI applications that run efficiently across devices.

The person in this role will own the SDK product vision, roadmap, developer workflows, technical requirements, and adoption strategy, working closely with engineering to turn complex AI infrastructure into clear, usable, well-documented developer tools.

This is a highly technical product role requiring hands-on coding ability, strong judgment around APIs and SDK design, and the ability to prototype, test, and critique developer experience flows directly.

The ideal candidate has built or managed developer tools, SDKs, APIs, AI platforms, or infrastructure products, and can operate credibly with senior engineers while also communicating product value to executives, partners, enterprise buyers, and external developers.

The goal of a Technical Product Manager is to bridge the gap between technical capabilities and business objectives, focusing on the technical aspects of product development. They work closely with engineering teams to define product roadmaps, prioritize features based on market research and customer needs, and ensure the successful delivery of technical products and services. In doing so, they manage the product vision, identify and mitigate potential risks, and maintain alignment with overall business requirements.

Responsibilities

• Product Vision & Strategy: Define and champion the product vision for the QVAC SDK, aligning technical capabilities with Tether s broader objectives around local AI, privacy, decentralization, and P2P infrastructure. Identify where the SDK should win across consumer app developers, enterprise AI teams, independent builders, and ecosystem partners.

• SDK Ownership: Own the roadmap for SDK capabilities, APIs, developer workflows, integrations, documentation, examples, templates, and tooling. Prioritize features that make it easier for developers to build, test, deploy, and scale Local AI applications using QVAC.

• Developer Experience: Curate the end-to-end developer experience, from first install to production integration. Design, mock up, and validate DevX flows including onboarding, SDK setup, API usage, CLI behavior, debugging workflows, sample apps, documentation journeys, and error states.

• Technical Product Definition: Translate product goals into precise technical requirements for engineering teams. Define SDK behavior, API surfaces, platform support, model/runtime constraints, performance expectations, privacy requirements, and integration patterns.

• Hands-On Prototyping: Use coding ability to explore SDK workflows, build proof-of-concept integrations, test APIs, review examples, evaluate documentation, and create credible technical prototypes or mockups using tools such as Cursor, Claude Code, GitHub, local scripts, notebooks, or lightweight apps.

• Engineering Partnership: Work closely with engineering leads to make informed product decisions around SDK architecture, model execution, edge inference, performance, packaging, platform compatibility, P2P networking, and developer ergonomics. Challenge assumptions constructively and help the team balance speed, usability, reliability, and technical debt.

• Market and Customer Understanding: Develop a strong understanding of the developer tools, AI infrastructure, Local AI, edge computing, and enterprise AI markets. Identify the needs of consumer application developers, enterprise customers, AI researchers, and platform partners, and convert those insights into roadmap priorities.

• Feature Prioritization: Prioritize SDK capabilities based on developer demand, technical feasibility, strategic value, adoption potential, and measurable business impact. Use data, user research, competitive analysis, and direct developer feedback to guide trade-offs.

• Documentation and Enablement: Partner with engineering, developer relations, and marketing to ensure the SDK has excellent documentation, examples, tutorials, migration guides, release notes, and launch materials. Ensure technical content is accurate, usable, and aligned with real developer workflows.

• Go-To-Market: Build and own SDK launch plans in partnership with marketing, developer relations, ecosystem, and business teams. Define positioning, target developer segments, adoption motions, enterprise use cases, and partner opportunities.

• Performance and Adoption Metrics: Define and track SDK success metrics, including activation, time-to-first-success, API usage, integration completion, retention, developer satisfaction, documentation quality, issue resolution time, performance benchmarks, and enterprise adoption.

• Stakeholder Communication: Communicate clearly with executives, engineers, partners, enterprise customers, and developers. Explain complex AI, SDK, and infrastructure concepts in ways that support decision-making, alignment, and adoption.