Lead AI DevOps Engineer

Overview

In this role you lead the technical direction for embedding AI into production-grade, API-first software platforms. You will guide cross-functional teams through architectural decisions and delivery, balancing innovation with pragmatism to ensure secure, operable systems. You’ll modernize legacy apps toward service-based architectures and shape integration patterns between AI services and platforms. This position offers real impact by aligning AI capabilities with reliable, scalable software delivery.

Responsibilities

• Provide technical leadership across AI-enabled software and DevOps engineering teams
• Set architectural direction for API-first design, system integration, and platform enablement for AI
• Lead modernization of legacy or existing applications toward service-based, API-driven architectures
• Define and guide integration patterns between applications, platforms, and AI services
• Decide on when/how emerging AI integration approaches (e.g., MCP) should be adopted
• Collaborate with architects, product teams, data scientists, and platform engineers to deliver end-to-end solutions
• Ensure solutions meet security, resilience, performance, and operability standards
• Anticipate and manage architectural and operational risks of AI-enabled systems
• Champion strong engineering practices across software development, DevOps, and platform engineering
• Lead by example in production-critical environments
• Delivery-focused leadership rather than experimentation for its own sake

Key requirements

• Senior or Lead Software Engineer, Lead DevOps Engineer, or similar hands-on leadership role
• Excellent software engineering fundamentals: system design, clean code, testing, long-term maintainability
• Deep experience designing and delivering API-driven and microservice-based systems
• Proven ability to modernise or integrate legacy systems into modern platforms
• Solid development experience in TypeScript and Python
• Experience spanning software delivery, CI/CD, infrastructure, and operations
• Comfortable setting direction and influencing teams without formal authority
• Ability to balance innovation with pragmatism in production environments

• strong technical credibility
• leadership without formal authority
• cross-functional collaboration
• API-driven design
• microservices
• TypeScript

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