Enterprise AI Portfolio Manager

Infoblox•Tacoma, WA

5d•Hybrid

About The Position

Infoblox is hiring an Enterprise AI Portfolio Manager in 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 view of delivery scope, priorities, timing, risks, dependencies, and results. The manager combines portfolio leadership with hands-on technical work, assessing requests, choosing appropriate AI approaches, and designing and building AI solutions from prototype through production. The role works with developers, business stakeholders, leadership, Enterprise Architecture, Security, Data, Infrastructure, and global teams to turn AI demand into a prioritized, capacity-aware roadmap of solutions that deliver measurable business value. It also establishes portfolio metrics and reusable practices, measures outcomes after launch, and communicates portfolio performance and recommendations to executives. The position is based in Tacoma. The posting lists a base salary of $122,000–$183,920 plus corporate bonus. Infoblox describes its work options as flexible, without specifying a particular work arrangement for this role.

Requirements

12+ years of experience in technology delivery, including hands-on building.
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, or 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 monitoring model quality, cost, and token usage.
Daily use of AI coding tools such as Claude Code, Cursor, OpenAI Codex, or GitHub Copilot.
Ability to plan capacity and make demand-versus-capacity trade-offs across internal and contractor teams.
Strong command of portfolio tooling and reporting, such as Jira, with a record of building dashboards used by leaders.
Experience defining and reporting delivery metrics and business value, rather than activity alone.
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 and maintain a single source of truth for initiative scope, priority, status, dates, dependencies, risks, and owners.
Design and build AI agents, assistants, and automated workflows using Anthropic Claude, OpenAI, Google Gemini, Glean, and AWS Bedrock, from prototype to production.
Use AI coding tools such as Claude Code, OpenAI Codex, Cursor, and GitHub Copilot to build and ship solutions faster.
Assess requests and select appropriate models, platforms, and agent patterns; evaluate feasibility, cost, effort, and risk before committing work.
Evaluate emerging models, agent frameworks, and AI tools, and recommend what to adopt.
Lead portfolio planning and prioritization with leadership and business stakeholders, balancing business value, effort, risk, and capacity.
Plan capacity across internal developers and contractor teams, adjusting 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 post-launch business value and report results against agreed success criteria.
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, establishing reusable patterns, standards, and best practices.