Senior Product Architect

Equinix•Redwood City, CA

6d•$213,000 - $319,000•Onsite

About The Position

Leads the vision, strategy, and execution for the AI Accelerators capability domain within Equinix Engineering Excellence (E3). This domain offers the connective layer between enterprise AI strategy and the practical operationalization of AI across engineering, product, infrastructure, and operations organizations. While every E3 capability domain is expected to embed AI into its respective developer experiences, workflows, and operational capabilities, this role is uniquely responsible for the broader AI-Driven Development Lifecycle (AI-DLC). This leader owns the strategy and roadmap for the foundational AI capabilities, platforms, orchestration frameworks, and reusable agent systems that enable product managers, architects, program managers, operations teams, and other non-developer personas to operate with AI-native workflows and materially higher leverage. The role is specifically accountable for: * Expanding the Internal Developer Platform (IDP) beyond traditional software developers to support non-developers building, configuring, deploying, and operating agents and AI-powered workflows * Defining the enterprise approach for human-agent collaboration patterns and AI-native operating models * Building the product management acceleration ecosystem, including agents that generate and refine product artifacts such as roadmaps, requirements, executive narratives, investment models, dependency analysis, adoption insights, and portfolio reporting * Establishing shared AI platform capabilities consumed across all E3 domains, including agent orchestration frameworks, context and knowledge management systems, and reusable workflow primitives The role requires balancing rapid AI innovation with governance, operational safety, trust, and measurable business outcomes while enabling Equinix to evolve toward an AI-native engineering and operational enterprise.

Requirements

15+ years of experience in product management, platform engineering, AI platform strategy, developer tooling, enterprise architecture, or engineering transformation
Experience leading large-scale AI transformation, developer platform, or intelligent automation initiatives
Strong understanding of AI-native development workflows, LLM-based systems, agent orchestration, and enterprise AI governance
Demonstrated experience driving cross-functional alignment across engineering, product, infrastructure, security, operations, and architecture organizations
Experience building developer and operational platforms that improve productivity, scalability, and organizational leverage
Strong executive communication and strategic planning skills
Experience with Agile product operating models and platform portfolio management
Familiarity with AI safety, model operations, prompt engineering, workflow orchestration, and human-in-the-loop operational models preferred
Bachelor’s degree preferred

Nice To Haves

Familiarity with AI safety, model operations, prompt engineering, workflow orchestration, and human-in-the-loop operational models

Responsibilities

Capability Domain Strategy & Vision: Defines and evolves the long-term vision, operating model, and roadmap for the AI Accelerators and AI-DLC capability domain, including: AI-native developer experiences and copilots, Agentic engineering workflows, AI-assisted software development lifecycle tooling, Product management acceleration agents, AI-driven backlog, roadmap, and requirements generation, AI-enabled architecture and dependency analysis, Intelligent workflow orchestration frameworks, AI workflow governance and safety controls, Autonomous and semi-autonomous remediation and operations, Prompt, context, and knowledge management frameworks, AI telemetry, evaluation, and optimization systems, Multi-agent collaboration and orchestration capabilities. Establishes strategic direction aligned to Equinix engineering productivity, operational scalability, developer experience, and enterprise AI transformation goals.
Product Portfolio Ownership: Owns a portfolio of AI-native platform products, agent frameworks, and AI-DLC capabilities, including roadmap prioritization, sequencing, dependency management, and adoption strategy. Ensures AI capabilities are reusable, scalable, governable, and embedded into day-to-day engineering and product workflows across the enterprise.
AI-Driven Product Management Transformation: Defines the strategy for AI-enabled product management and portfolio operations, including the agents and workflows required to scale product leadership effectiveness. Owns capabilities for: Automated product requirement and PRD generation, Executive narrative and inspection artifact generation, Roadmap synthesis and dependency analysis, Investment and business case generation, Capability decomposition and scoping assistance, Product telemetry summarization and insight generation, Adoption and Voice of Developer insight synthesis, Portfolio prioritization and scenario modeling, AI-assisted backlog refinement and epic creation, Product operations and governance automation. Partners with product, engineering, architecture, and portfolio management leaders to redefine how product work is created, governed, and operationalized in an AI-native organization.
Executive Inspection Leadership: Partners with engineering, architecture, product, and operational leaders to shape and govern the executive inspection process for the AI Accelerators domain. Drives alignment between AI investment strategy, operational readiness, governance, and measurable business outcomes.
AI-Native Developer & Operator Experience Leadership: Represents the needs of developers, product managers, architects, SREs, security engineers, and operational teams adopting AI-native workflows. Partners with Voice of Developer and AI adoption programs to improve usability, trust, discoverability, and operational effectiveness of AI capabilities.
Cross-Functional Platform Leadership: Works across E3, Engineering, Infrastructure, Security, Architecture, SRE, Product, and Operations organizations to align AI strategy and execution. Acts as the connective layer between enterprise AI strategy, platform architecture, and operational execution.
Financial & Investment Planning: Develops business cases and investment strategies for AI-native engineering and operational capabilities. Understands the economics of AI-assisted engineering, agent orchestration, inference consumption, workflow automation, and organizational productivity scaling.
Product & Adoption Metrics: Defines and governs KPIs for AI Accelerators and AI-DLC effectiveness. Uses telemetry and analytics to continuously improve AI workflows, platform experiences, and organizational effectiveness.
Agile Product & Engineering Partnership: Partners closely with engineering, architecture, AI platform, and operational leaders to define execution priorities and delivery sequencing. Ensures AI initiatives remain measurable, outcome-oriented, governable, and aligned to enterprise priorities.