AI Product Manager

Responsibilities

• Strategic Planning and Roadmap: Defining and communicating the AI product vision and strategy aligned with company objectives. Identifying market opportunities, prioritizing features, and driving AI applications to enhance business operations.

• Product Development and Execution: Developing AI products hands-on, including coding and prototyping, while collaborating closely with other teams (DevOps, SRE, Admins, and product teams) to ensure alignment with technical feasibility and business requirements. Actively leading the recruitment process for the growing AI team, including crafting and evaluating technical assessments, interviewing candidates, and onboarding new team members.

• Data-Driven Analysis and Continuous Improvement: Monitoring product performance, defining KPIs, and leveraging user analytics to evaluate effectiveness and drive continuous improvements.

• Stakeholder Collaboration and Go-to-Market: Serving as the primary liaison between technical teams and business stakeholders, coordinating go-to-market strategies, managing external partnerships, and ensuring effective product documentation and communication.

• Innovation and Future Development: Keeping abreast of emerging AI technologies, promoting innovation, and incorporating new methodologies to maintain competitive advantages and product differentiation.

Achievements

• AI Localisation Assistant (AILA): Delivered an innovative AI-powered localization tool that significantly reduces translation time from days to minutes while maintaining consistent brand voice across multiple markets. AILA utilizes approved terminology and translation memory, greatly reducing manual editing and costs. Evaluations demonstrated superior median scores in naturalness and clarity compared to other automated solutions.

• AI Retrieval API (AIR API): Developed a robust AI-driven retrieval service providing advanced document retrieval capabilities for internal knowledge bases. Implemented a graph-based workflow leveraging modern AI frameworks and databases for effective semantic search and query decomposition. Currently expanding the API to include integrations with task tracking systems and modern AI context management protocols.

• Spotware Agent Service: Developed and prepared for deployment a scalable platform for hosting and serving AI agents. The service supports asynchronous processing, data streaming, and a modular architecture, enabling seamless integration of diverse AI agents into various business workflows.

• AI Spec Assistant (AISA): Developed and deployed an advanced AI assistant designed for analyzing, validating, and refining requirements and specifications. Hosted on the Spotware Agent Service, AISA supports iterative feedback loops, automated topic research, and semantic analysis, enhancing the quality and accuracy of project documentation and reducing manual analysis efforts.