AI Product Manager

Job Description

Strategic Staffing Solutions is currently looking for an AI Product Manager , for a W2 contract opportunity!

AI Product Manager

Location: Charlotte, NC or Dallas, TX

Work Schedule: Hybrid

Duration: 12 months

This is a W-2 contract opportunity, and candidates must be able to work on our W-2 only. NO C2C or 1099.

Top Skill:

• Should have some AI experience- ideally worked in AI product org or at least some AI products works
• Years of Experience Required? 5-7
• Prior Banking domain experience is nice to have.

Job Summary:

We are hiring a Senior Product Manager to own an AI end user tooling product end-to-end - from discovery and strategy through delivery, launch, and continuous iteration. This role sits within the AI End User Tooling organization and is accountable for building intelligent, AI-powered experiences that meaningfully improve how knowledge workers get their jobs done.

The right candidate combines deep product instinct with genuine AI fluency. They understand both the art of crafting delightful end-user experiences and the science of working with modern AI models. They are comfortable making trade-offs across user value, technical feasibility, business outcomes, and responsible AI considerations.

Key Skills:

Product Management Fundamentals

• End-to-end ownership - demonstrated track record of taking a product from idea to launch and through multiple iterations.
• Customer obsession - deep empathy for end users and a habit of grounding decisions in user evidence.
• Prioritization - ability to say no thoughtfully and focus a team on the highest-leverage work.
• Strategic thinking - able to zoom out to vision and zoom in to release-level decisions fluidly.
• Written communication - writes crisp PRDs, narratives, and decision documents that scale across the org.

AI & Technical Fluency

• LLM literacy - understands modern foundation models, their capabilities, limitations, and failure modes.
• Prompt and evaluation design - can shape prompts, define evaluation rubrics, and reason about model quality trade-offs.
• AI UX patterns - fluent in modern AI interaction patterns: chat, agents, copilots, structured outputs, tool use, and human-in-the-loop.
• Engineering partnership - can read system designs, ask sharp technical questions, and credibly partner with engineers.
• Responsible AI - understands risk surfaces: hallucination, bias, privacy, security, and over-reliance.

User Experience & Design Sense

• Design partnership - collaborates as a peer with designers on flows, prototypes, and interaction details.
• Quality bar - holds a high bar for craft, polish, and user-perceived quality.
• Accessibility & inclusion - considers a broad range of users in design decisions.

Data & Analytics

• SQL or equivalent - can pull and explore product data without depending on others.
• Experimentation - designs and interprets A/B tests, offline evaluations, and structured pilots.
• Metrics design - defines input, output, and guardrail metrics that drive the right behavior.

Leadership & Communication

• Executive communication - tailors message and depth for the audience, from working groups to senior leaders.
• Influence without authority - drives alignment across partner teams and functions.
• Bias to action - moves with urgency while maintaining quality and judgment.
• Ownership mindset - treats outcomes - not output - as the measure of success

" Beware of scams. S3 never asks for money during its onboarding process ."