Distinguished Engineer

About the role

This role combines deep technical expertise with the ability to influence engineering direction through implementation, mentorship, innovation, and company-wide technical leadership. You will play a critical role in accelerating strategic initiatives, incubating greenfield capabilities, and modernizing engineering practices through AI-assisted software development workflows.

Responsibilities

• Lead the design and implementation of scalable Product Access and entitlement systems supporting cloud, API, and AI-driven products
• Define and drive the long-term technical strategy and engineering vision for Product Access platforms and access enforcement capabilities
• Drive the development of greenfield initiatives and foundational platform capabilities through hands-on prototyping and implementation
• Serve as a technical accelerator across teams by contributing directly to critical projects and resolving complex engineering challenges
• Champion adoption of AI-assisted software development practices, including effective use of tools such as Claude Code to improve engineering productivity, software quality, and delivery velocity
• Establish best practices for integrating AI-assisted workflows into software design, implementation, testing, and operational support
• Design systems supporting access decisions for both human and non-human actors, including services, automations, and AI agents
• Build highly scalable, low-latency, and resilient distributed systems with strong operational excellence
• Influence technical direction across multiple engineering organizations to drive adoption of shared platform capabilities, standards, and engineering practices
• Build strong partnerships across engineering, product, security, and business teams while constructively challenging decisions when needed to ensure long-term scalability and company-wide alignment
• Act as a company-level technical leader, making decisions and recommendations based on what delivers the greatest overall customer and business impact
• Possess a deep understanding of SaaS licensing and entitlement models
• Drive enterprise-scale platform adoption and technical convergence initiatives

Requirements

• 12+ years of experience building large-scale distributed systems and platform services
• Strong hands-on software engineering background with the ability to contribute directly to architecture, design, and implementation
• Proven experience building or evolving: Product Access platforms, entitlement and licensing systems, usage-based or consumption-driven services
• Deep expertise in: Cloud-native architectures, distributed systems design, microservices and API design, scalability, reliability, and operational excellence
• Recognized technical expertise in distributed systems, platform engineering, or Product Access architectures
• Demonstrated ability to shape engineering direction through technical vision, innovation, and influence
• Strong experience driving engineering productivity improvements through modern tooling and developer platform investments
• Practical experience leveraging AI-assisted software development workflows and tools such as Claude Code, GitHub Copilot, Cursor, or similar technologies in real-world engineering environments
• Familiarity with AI-enabled product patterns, agentic workflows, and API-driven consumption models
• Proven ability to influence technical strategy and drive alignment across multiple organizations without direct authority
• Strong executive communication and stakeholder management skills, with the ability to navigate complex organizational and technical tradeoffs
• Demonstrated ability to balance short-term delivery pressures with long-term platform and architectural sustainability
• Strong product and business acumen, with the ability to align technical decisions with customer and business outcomes

Qualifications

• Experience with SaaS licensing and entitlement models
• Experience building platform services used across multiple engineering organizations
• Exposure to developer platforms, internal tooling, or engineering productivity initiatives
• Experience with Kubernetes, event-driven architectures, and modern cloud platforms (AWS, Azure, or GCP)
• Exposure to AI/ML-enabled products and modern AI application architectures
• Experience driving enterprise-scale platform adoption and technical convergence initiatives