Senior AI Product Manager - Agentic AI & Data Intelligence

Lead strategy and delivery of agentic AI and data intelligence products that turn emerging enterprise data and AI capabilities into secure, scalable, measurable outcomes.

Responsibilities

• Define and evolve product strategy and roadmaps for Agentic AI and Data Intelligence products and platforms
• Research emerging technologies, industry standards, architectures, and best practices across AI agents, multi-agent systems, LLMs, reasoning models, tool use, and workflow orchestration
• Explore how AI agents can automate complex workflows, augment decision making, and improve user interaction with enterprise data
• Translate new technical capabilities into enterprise use cases, product investments, and roadmap priorities
• Own technical product requirements including capabilities, APIs, integration patterns, success metrics, and non-functional requirements
• Partner with engineering, architecture, data science, data engineering, security, and business teams to move capabilities from concept to production
• Define reusable platform capabilities for agent orchestration, tool integration, context management, memory, data access, reasoning, and human-in-the-loop workflows
• Drive build vs buy vs partner decisions for emerging AI and data technologies
• Define product capabilities across structured and unstructured data, semantic search, metadata, knowledge retrieval, RAG, vector search, and natural-language data interaction
• Support hands-on PoCs and prototypes for single-agent and multi-agent workflows, tool calling, APIs, enterprise data sources, and automated business processes
• Define experiment hypotheses, evaluation datasets, success criteria, and production-readiness requirements
• Assess agent performance across task completion, accuracy, reasoning quality, latency, cost, reliability, security, and user experience
• Establish evaluation and benchmarking frameworks for agentic AI beyond traditional model-level metrics
• Partner with risk, security, privacy, and governance teams to establish controls for autonomous and semi-autonomous AI systems
• Create technical assessments, product requirements, architecture recommendations, benchmarking reports, decision documents, and technology landscape analyses
• Communicate product strategy, technical trade-offs, investment requirements, and measurable business outcomes to technical and executive stakeholders

Requirements

• Significant experience in AI product management, data platform product management, or related technical roles
• Strong understanding of Generative AI, LLMs, Agentic AI architectures, RAG, enterprise search, APIs, and modern data platforms
• Understanding of agent concepts: tool/function calling, planning, reasoning, context management, orchestration, memory, and human-in-the-loop patterns
• Experience working with structured and unstructured enterprise data, data APIs, metadata, search, retrieval, or analytics platforms
• Strong technical fluency with REST APIs, JSON, Python (or similar scripting languages), cloud platforms, and AI/ML services
• Demonstrated ability to define technical products and collaborate deeply with engineering, architecture, data science, and data engineering teams
• Experience evaluating emerging technologies through PoCs, experimentation, benchmarking, and structured technical analysis
• Strong written and verbal communication skills to translate complex AI and data concepts into clear product and executive recommendations
• Experience designing or delivering enterprise AI agents, copilots, intelligent workflow automation, or AI-powered data products
• Experience with agent development and orchestration frameworks and emerging interoperability standards such as MCP
• Familiarity with vector databases, knowledge graphs, semantic layers, embedding models, enterprise search, data catalogs, and modern data platforms
• Experience developing evaluation frameworks for LLMs and agentic systems, including automated evaluation and human evaluation
• Understanding of enterprise AI governance, data governance, security, privacy, responsible AI, identity/access management, and observability
• Experience moving emerging AI capabilities through research to experimentation to PoC to production to scaled enterprise adoption

Location and Pay

• Phoenix, AZ (onsite)
• Base salary: USD 100,000 - 140,000 per year
• Work mode: onsite
• Pay details: $100K-$140K /Yr Base + Annual Bonus

Technologies

• REST APIs, JSON, Python
• LLMs, RAG, vector search, enterprise search
• Tool/function calling, workflow orchestration, multi-agent systems
• MCP, vector databases, knowledge graphs, semantic layers, embedding models
• Data catalogs, identity/access management, observability