• Architect, strategize, and execute the enterprise technical roadmap for AI-driven software development tools.
  

• Assess emerging AI technologies and developer utilities against organizational requirements, technical constraints, information security protocols, and total cost of ownership.
  

• Design, build, and deliver functional prototypes, custom integration pipelines, and reference implementations to transition AI capabilities into production workflows smoothly.
  

• Embed AI tooling directly into developer workstations, IDE ecosystems, source code management, and automated CI/CD pipelines.
  

• Partner with cross-functional governance stakeholders (Enterprise Security, IT, Legal, and Compliance) to enforce strict controls around IP protection, access management, and licensing.
  

• Establish standardized frameworks, configuration best practices, and integration blueprints for widespread engineering adoption.
  

• Champion organizational enablement through hands-on technical workshops, comprehensive documentation, and direct pairing with engineering squads.
  

• Define and track core KPIs centered on platform adoption rates, developer experience (DevEx), codebase quality, and delivery velocity.
  

• Continuously monitor advancements in the LLM and autonomous tooling landscape to identify and operationalize new capabilities.
  

Requirements

• Proven background in software engineering, advancing into hands-on solution architecture or technical leadership roles.
  

• Demonstrated, recent experience integrating Generative AI tools and autonomous workflows into everyday software engineering lifecycle.
  

• Practical, hands-on familiarity with modern AI coding assistants (e.g., Cursor, Claude Code, GitHub Copilot, or equivalent platforms).
  

• Strong programming capabilities with the ability to write robust, production-grade code, build extensible tool integrations, and validate architecture through working code.
  

• Solid technical grasp of enterprise ecosystem fundamentals, including modern IDEs, REST/gRPC APIs, IAM/SSO, version control, and CI/CD pipelines.
  

• Deep comprehension of LLM behaviors, model context handling, tool execution/calling, and multi-agent systems.
  

• Proven ability to evaluate complex engineering trade-offs regarding security posture, operational costs, system scalability, and developer ergonomics.
  

• Excellent interpersonal and stakeholder communication skills, with the ability to bridge technical and business domains.
  

• Ability and willingness to work on-site at the Eindhoven facility 2 to 3 days per week.
  

Preferred Qualifications:

• Prior track record deploying developer platforms, productivity tooling, or AI services at an enterprise scale.
  

• Experience connecting LLMs/agents with proprietary internal knowledge bases, private code repositories, and engineering data backend.
  

• Familiarity with the Model Context Protocol (MCP), custom agent frameworks, or bespoke IDE extension development.
  

• Domain exposure to embedded software engineering, semiconductor workflows, or complex hardware-software integration pipelines.
  

• Experience architecture qualitative and quantitative developer productivity metrics and software quality benchmarks.
  

Benefits