Senior AI Product Manager

Senior AI Product Manager

Location: Phoenix, AZ,

Duration: Long Term Contract

Max Rate : $55/hr W2

Employment: W2 Only —

No C2C, C2H, or 1099

Work Authorization: USC / Green Card Holders only

We are seeking an AI Product Managerto drive productstrategy, research, evaluation, and direction for AI-powered Document Intelligence capabilities. This role combines technical product management, market and technology research, and hands-on evaluation of AI solutions.

The ideal candidate will have a strong understanding of Agentic AI, Generative AI, LLMs, multimodal models, OCR, document parsing and extraction, retrieval technologies, with the technical depth to evaluate solutions, design experiments, support Proofs of Concept, and translate findings into product and technology recommendations.

Responsibilities

• Research emerging trends,technologies, industry standards, and best practices across Document Intelligence, Agentic AI, Generative AI, multimodal AI, OCR, document understanding, extraction, classification, retrieval and authentication.
• Evaluate third-party tools,open-source technologies, foundation models, and cloud-native AI services to identify opportunities for new or improved capabilities.
• Translate technology developments into actionable productstrategies, investment recommendations, and roadmap opportunities.
• Own technical productstrategy, requirements, and roadmap development for Document Intelligence capabilities.
• Define product requirements, technical capabilities, APIs,integration patterns, successmetrics, and non-functional requirements in partnership with engineering and architecture teams.
• Serve as the bridge betweenbusiness, engineering, data science, architecture, and AI/ML teams, translating complex technical concepts into clear product decisions.
• Evaluate build-vs-buy-vs-partner opportunities and articulate associated technical and product trade-offs.
• Develop structured evaluation frameworks and benchmarks for comparing AI models, platforms, and Document Intelligence solutions.
• Design and executeexperiments measuring factorssuch as accuracy, extraction quality,latency, scalability, reliability, cost, integration complexity, and model performance.
• Establish repeatable benchmarking methodologies and maintaina fact-based view of the competitive and technology landscape.
• Partner closely with engineers and data scientists to design and execute PoCs, prototypes, and technical experiments for emerging AI technologies.
• Define PoC hypotheses, datasets, evaluation criteria,success metrics, and recommendations for production adoption.
• Identify technical risks,limitations, dependencies, and scaling considerations before solutions progress toward production.
• Produce high-quality technical assessments, benchmarking reports,architecture/product recommendations, decision documents, and technology landscape analyses.
• Synthesize complex researchand experimental resultsinto clear recommendations for both technical teams and senior leadership.
• Maintain reusable documentation covering evaluated technologies, benchmarks, lessons learned, and technology decisions.
• Develop executive-ready materialsthat clearly communicate opportunities, trade-offs, risks, investment considerations, and recommended next steps.

Qualifications

• Significant experience in technical or AI productmanagement, ideally involvingDocument Intelligence.
• Strong knowledge of Agentic AI, Generative AI, LLMs, multimodal models, OCR, information extraction, and RAG/retrieval.
• Understanding of tool calling, planning,reasoning, orchestration, memory,context management, and human-in-the-loop patterns.
• Experience defining technical products and requirements with Business, Engineering, Architecture, Security, and Data Science teams.
• Demonstrated ability to use experimentation and quantitative evaluation to inform product decisions.
• Experience assessing vendors,emerging technologies, and build-vs-buy alternatives.
• Familiarity with AI evaluation methodologies, including ground-truth datasetcreation, accuracy metrics, model evaluation, latency/cost analysis, and quality measurement.
• Understanding of enterprise security, privacy, responsible AI, governance, scalability, and observability.
• Excellent analytical and written communication skills, with demonstrated ability to create technical documentation, research reports, product requirements, and executive-level recommendations.