Senior Product Manager

Title: Senior Product Manager

Work location: Orlando, FL 2 day Onsite in week

Ideal Start Date:  ASAP

Duration of Assignment: 23+ months

W2 Only  

Top skills sets needed: BS, KPIs, OKRs, Direct exposure to one or more of: LiteLLM or a comparable LLM gateway, Open WebUI or a comparable chat experience, n8n or a comparable workflow runtime, modern agentic frameworks (LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or similar), Arize / Phoenix / Langfuse or comparable evaluation tooling, MCP (Model Context Protocol). using AI coding assistants (Claude, Cursor, or similar) to build and ship real solutions, not just experiment.

EXTERNAL JOB DESCRIPTION:

The company’s proprietary AI provides endpoints to AI models and agents, SDKs and integrations, observability, governance, and enterprise knowledge connections — enabling teams across the company to build AI-driven solutions safely, efficiently, and at scale. The stack includes an AI gateway, a chat experience layer, a workflow and agent runtime, Model Context Protocol (MCP) services, retrieval-augmented generation (RAG) integrations, and AI observability and evaluation tooling.

We are seeking a Senior Product Manager to define and deliver high-impact AI solutions on Jedai, and through that work to grow the platform’s adoption and impact across the enterprise. This is a product role first: you own the path from a stakeholder’s first conversation to an adopted, measured AI solution — leading discovery, framing the problem, setting product direction, defining what success looks like, and partnering closely with Engineering and Operations to see it through to delivery. You will also use AI tooling to prototype and assemble working solutions quickly — to validate ideas with stakeholders and show them what’s possible on the platform, and to drive your own and the team’s productivity gains. Working with the best and latest AI available also keeps you close to what the industry is producing, so you can recognize when a capability has matured into an opportunity worth pursuing.

What You’ll Do

•              Own the product lifecycle for a set of Jedai use cases end-to-end: from the first stakeholder conversation through an adopted, measured solution.

•              Lead discovery: run user interviews, focus groups, and surveys; talk to users directly to understand what they’re trying to achieve and where the platform can help.

•              Define and track success: set KPIs and OKRs, define the success metrics for your use cases and for the team, and report on whether the work is delivering against them.

•              Contribute to the product roadmap: bring evidence from stakeholder conversations and usage data to shape what the platform and the team build next.

•              Build prototypes, demos, and working solutions on Jedai — prompts, agents, retrieval, n8n-style workflows, and MCP integrations — to make a capability tangible, validate the approach, and onboard stakeholders onto the platform.

•              Share work-in-progress at ~70% to gather stakeholder feedback and iterate, rather than holding work until it’s polished.

•              Stay at the forefront of AI: test and experiment with the latest models, tools, and techniques, and help the team decide where it’s worth investing now versus waiting for the industry to converge.

•              Manage stakeholder expectations and relationships: keep both technical and non-technical partners informed and confident throughout the use-case lifecycle.

•              Communicate tradeoffs, progress, and outcomes to senior stakeholders, connecting platform capability to business results in language each audience understands.

•              Operate independently in a low-structure environment: know when to cut scope, when to ship, and when to ask for input.

Basic Qualifications

•              Bachelor’s degree in Computer Science, Information Systems, Engineering, a related field, or comparable work experience.

•              5+ years of Product Management experience, including direct, end-to-end ownership of a stakeholder-facing or internal-customer-facing product.

•              Strong track record running product discovery — user interviews, focus groups, surveys, and direct user engagement — to define problems and validate solutions.

•              Experience defining and delivering on success metrics (KPIs, OKRs) and contributing to a product roadmap.

•              Excellent communication and stakeholder-management skills, including building trust with senior leaders across both technical and non-technical audiences and translating AI capability into business outcomes.

•              Hands-on capability to prototype and build working solutions using AI tooling — prompts, agents, retrieval, and workflow/agent runtimes.

•              Familiarity with AI and machine learning concepts: LLM applications, prompt engineering, agents, retrieval-augmented generation, and model catalogs.

•              Demonstrated judgment in scope, speed, and quality tradeoffs: knowing when to ship at 70% to learn fast, when to harden, and when to drop work that isn’t paying off.

•              Genuinely excited to work at the forefront of AI — energized by experimenting with what’s new and turning it into a clear point of view the team can act on.

Preferred Qualifications

•              Direct exposure to one or more of: LiteLLM or a comparable LLM gateway, Open WebUI or a comparable chat experience, n8n or a comparable workflow runtime, modern agentic frameworks (LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or similar), Arize / Phoenix / Langfuse or comparable evaluation tooling, MCP (Model Context Protocol).

•              A track record of using AI coding assistants (Claude, Cursor, or similar) to build and ship real solutions, not just experiment.

•              Experience running an early-adopters, pilot, or design-partner program with measurable adoption outcomes.

•              Background partnering with senior leaders to turn business problems into shipped AI capabilities.

•              Familiarity with enterprise governance, security, and compliance patterns for AI systems