Head of DevOps and Analytics

Key Responsibilities

• Define and execute the enterprise strategy and roadmap for DevOps, Platform Engineering, AI Ops, developer experience, and engineering productivity.
• Build the IDP as a product, providing self-service infrastructure, environments, reusable capabilities, golden paths, and standard toolchains that reduce cognitive load for engineering teams.
• Lead AI Ops and Agentic DevOps adoption across planning, coding, review, testing, deployment, incident response, governance, and continuous improvement.
• Establish governance for AI models, agents, generated code, orchestration, security, compliance, auditability, enterprise AI gateways, MCP integrations, and observability.
• Own CI/CD and DevSecOps standards, embedding automated SAST, SCA, DAST, secrets detection, software supply chain security, policy enforcement, and compliance throughout the SDLC.
• Set cloud reliability, resilience, performance, disaster recovery, observability, incident management, SLI/SLO, and error-budget practices, including automated remediation and self-healing capabilities.
• Define engineering metrics and dashboards covering platform adoption, deployment frequency, lead time, reliability, security, developer experience, and productivity.
• Build and mentor high-performing DevOps, Platform, SRE, and AI Ops teams while managing budgets, vendors, partnerships, and organizational change.
• Ability to work effectively with distributed global teams across multiple time zones and collaborate with stakeholders at different organizational levels.

Qualifications and Skills

• Master’s or Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; Master's degree or relevant certifications preferred.
• 12+ years in software engineering, infrastructure, cloud, or DevOps, including 10+ years leading DevOps, Platform Engineering, SRE, or Cloud Operations teams.
• Proven success building enterprise engineering platforms, leading cloud transformation, implementing DevSecOps, and modernizing ways of working.
• Experience leading globally distributed teams and communicating effectively with technical, security, product, and executive stakeholders.
• Hands-on experience with AI-powered engineering workflows, coding assistants, autonomous agents, LLM operations, AI governance, and operational controls.
• Working knowledge of MCP servers, agentic workflows, tool integrations, retrieval systems, AI observability, and responsible AI risk management.
• Microsoft Certifications AZ-204 or AZ-400 are a big advantage.

Technical Knowledge

Leadership Competencies