Accountabilities:

Technical Vision and Strategic Leadership: Define and communicate the multi-year technical vision for the Builder Platform, translating organizational strategy into a clear roadmap covering AI agents and workflows, AI infrastructure, developer infrastructure, and productivity engineering.
Lead major cross-functional technical initiatives, ensuring alignment between engineering teams, business stakeholders, and organizational priorities.
Establish architectural standards, technical principles, and clear ownership boundaries that support sustainable platform development and adoption.
Agent Platform and AI Infrastructure: Lead the architecture, development, and evolution of the shared Agent Platform, enabling teams to deploy, operate, evaluate, govern, and continuously improve AI agents and automated workflows.
Design and operate centralized Large Language Model (LLM) and Model Context Protocol (MCP) gateways, establishing appropriate guardrails, fallback mechanisms, usage monitoring, cost controls, model rollout policies, and Service Level Objectives (SLOs).
Implement AI governance frameworks in collaboration with Security, Legal, and IT teams, translating organizational policies into practical controls, approved usage patterns, and auditable processes.
Architect intelligent agents and workflows that automate engineering activities from issue identification to production deployment, as well as business processes from initial triggers to measurable outcomes.
Determine which agentic capabilities should become standardized platform services and which should remain independently managed by individual teams.
Developer Infrastructure and Productivity Engineering: Own the technical strategy for developer infrastructure, including source control systems, Continuous Integration (CI), repository standards, access management, ownership models, and reusable workflows.
Improve CI reliability, infrastructure efficiency, and developer experience by reducing friction and optimizing engineering processes.
Define and implement standardized approaches to agentic development tools, including best practices, reusable workflows, enablement resources, and internal adoption strategies.
Drive organization-wide adoption of AI-powered coding tools and agentic technologies through collaboration, influence, and practical enablement rather than rigid mandates.
Cross-Functional Collaboration and Governance: Partner with senior stakeholders across Engineering, Product, Sales, and General and Administrative (G&A) functions to identify opportunities where AI and automation can improve business outcomes.
Prioritize strategic initiatives into a coordinated company-wide technical portfolio.
Define which capabilities should be centralized, standardized, delegated to individual teams, purchased externally, or deliberately excluded from development.
Balance speed, flexibility, reliability, security, cost, and long-term maintainability when making complex architectural and organizational decisions.
Establish governance through standardized tools, approved workflows, and practical implementation patterns that encourage adoption without creating unnecessary bureaucracy.
Performance Measurement and Continuous Improvement: Define outcome-oriented metrics to measure platform adoption, engineering velocity, reliability, quality, and infrastructure costs.
Establish feedback loops that quantify productivity improvements and provide actionable insights for roadmap prioritization.
Use performance data and stakeholder feedback to identify systemic issues and continuously improve platform capabilities.
Product Strategy and Open-Source Contributions: Lead the internal customer-zero strategy, using real organizational implementations to validate platform capabilities and identify opportunities for product improvement.
Translate internal experience into validated technical requirements for cloud products, software development kits (SDKs), and agent development frameworks.
Maintain a continuous feedback loop with product leadership to influence product strategy and development priorities.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1