Product Manager - AI Platform
Overview:
As a Product Manager (level to be determined by experience) for the Data Solutions business, you will own the technical direction of Data Solutions on Precisely’s AI Studio, and support contribute to the overall Data API, Cloud and SaaS strategy. You will set the roadmap and drive the engineering understanding of the backlog for Precisely’s hosted MCP Server, Skills, Agents and Apps. Additionally, you will assist with technical requirements, development resources and documentation for Precisely Data APIs. This is a hands-on, technical role at the intersection of Product Management and Engineering: you will become the subject matter expert on our technology, define acceptance criteria, consult on sprint priorities, resolve customer escalations, and make the daily calls that keep multiple engineering teams delivering results. You will partner closely with customers, support, QA, and the broader Product team to create Data Solutions for real-world addressing business challenges.
What you will do:
Be the technically oriented subject matter expert for all Data Solutions and content on AI Studio, the modern developer portal
Serve as a subject matter expert on AI integration with Precisely Data focusing on APIs, MCP Server, Skills, Agents and Apps
Use AI tools to build and test prototype solutions to prioritized business problems
Work closely with Sales Engineers to validate proposed solutions for field verified use cases
Create detailed engineering requirements to convert prototypes into hardened products
Perform industry and market research to stay informed of technological advancements in AI to identify revenue opportunity and to apply best practices to Precisely solutions
Own and prioritize the backlog across multiple engineering teams, covering new features, enhancements to existing features. You will assist and advise the engineering team on their defects and technical debt considerations.
Provide subject matter expertise to the support team as they handle customer escalations, this could be from initial triage on accounts through to engineering root-cause analysis, fix validation, and customer-facing resolution.
Act as the technical bridge between Product, Engineering, QA, Support, and external customers – running weekly review calls and contributing to solution definition reviews.
Advise on communications, release-notes and other documentation.
What we are looking for:
Atleast 5 years of professional experience in a technical role (software development, solutions engineering, data analytics, QA, or similar)
Strong foundational knowledge of AI tools, integrations, and the modern AI ecosystem — including LLMs, AI agents, MCP servers, and API-based developer tooling
Hands-on experience using AI tools (Claude, Copilot, ChatGPT, or equivalent) to build, test, or evaluate solutions — whether through coursework, personal projects, internships, or work experience
Ability to read and understand REST API documentation, basic software architecture concepts, and technical design discussions
Strong written and verbal communication skills — comfortable translating technical concepts for both engineering and business audiences
Demonstrated curiosity and self-driven learning in the AI/ML space
Some international travel maybe required.
AI/Skills Knowledge:
Coursework, certifications, or hands-on project experience with AI/ML technologies, prompt engineering, or agent-based architecture
Comfort using AI tools to accelerate work — drafting requirements, reviewing code, testing outputs, or prototyping solutions
Familiarity with concepts such as MCP servers, AI agents, skills/apps frameworks, or LLM APIs is a strong differentiator
Preferred Skills (a plus but not required):
Internship or project experience in product management, business analysis, or solution engineering
Experience working with GraphQL APIs — querying, schema exploration, or integration testing
Exposure to location data, address geocoding, GIS, or data quality concepts
Experience with hyperscaler platforms (AWS, Azure, GCP) or API marketplace ecosystems
Understanding of how agent-native API architectures affect product and developer experience
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