Enterprise AI Portfolio Manager

Infoblox•Tacoma, WA

7d•$122,000 - $183,920•Hybrid

About The Position

Infoblox is seeking an Enterprise AI Portfolio Manager to join its IT organization in Tacoma. Reporting to the Senior Director, Enterprise AI, this role owns the Enterprise AI portfolio and provides leadership with a clear, trusted view of delivery scope, timing, and results. The role combines portfolio management with hands-on technical work: assessing requests, designing suitable approaches, and building AI solutions. The manager will collaborate with developers, business stakeholders, leadership, Enterprise Architecture, Security, and Data teams, as well as global teams. The goal is to turn AI ambitions into a prioritized, well-managed portfolio of working solutions that deliver measurable business value. The role also establishes reusable practices and improves how AI work is planned, built, and shipped.

Requirements

12+ years of experience in technology delivery, including hands-on building, and 5+ years leading portfolio or program management across multiple teams.
2+ years of hands-on experience building generative and agentic AI solutions with frontier models such as Anthropic Claude, OpenAI GPT, Glean, and Google Gemini.
Hands-on experience with AI cloud platforms such as AWS Bedrock, Azure AI Foundry, and Google Vertex AI.
Experience with agent frameworks and protocols such as Claude Agent SDK, OpenAI Agents SDK, LangGraph, Model Context Protocol (MCP), and Agent2Agent (A2A).
Strong understanding of prompt and context engineering, retrieval-augmented generation (RAG), vector databases, tool use, and multi-agent orchestration.
Experience with AI evaluation, observability, and guardrails, including tracking model quality, cost, and token usage.
Daily use of AI coding tools such as Claude Code, Cursor, OpenAI Codex, or GitHub Copilot.
Proven ability to plan capacity and make trade-offs between demand and capacity across internal and contractor teams.
Strong command of portfolio tooling and reporting, such as Jira, and a track record of building dashboards that leaders use.
Experience defining and reporting delivery metrics and business value, not just activity.
Proven ability to influence senior leaders and make clear prioritization recommendations when priorities compete.
Experience preparing QBRs and executive readouts, with strong storytelling, presentation, and writing skills for executive and C-level audiences.
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.

Nice To Haves

PMP, PgMP, SAFe, or equivalent certification.

Responsibilities

Own the Enterprise AI portfolio end to end, maintaining a single source of truth for each initiative’s scope, priority, status, dates, dependencies, risks, and owners.
Design and build AI agents, assistants, and automated workflows hands-on, from prototype through production.
Use AI coding tools to build and ship solutions more efficiently.
Assess the AI approach for each request, selecting suitable models, platforms, and agent patterns, and evaluating feasibility, cost, effort, and risk before committing work.
Evaluate new models, agent frameworks, and AI tools and recommend which to adopt.
Lead portfolio planning and prioritization with leadership and business stakeholders, balancing value, effort, risk, and available capacity.
Plan capacity across internal developers and contractor teams and adjust as demand changes.
Build and maintain the Enterprise AI roadmap, translating company priorities into a sequenced delivery plan.
Manage cross-team dependencies and risks with Enterprise Architecture, Security, Data, Infrastructure, and business teams.
Define and report portfolio metrics, including throughput, cycle time, on-time delivery, and capacity utilization.
Measure business value after launch and report results against success criteria agreed at the outset.
Prepare and lead Quarterly Business Reviews covering portfolio performance, value delivered, roadmap progress, capacity, and upcoming priorities.
Deliver executive readouts to IT and company leadership, presenting portfolio data, decisions needed, and recommendations clearly.
Provide regular status updates to executive sponsors and raise risks early with options and recommendations.
Improve how the team plans, builds, and ships AI work, and establish reusable patterns, standards, and best practices.