Assignment Description

We are looking for a Project manager.

Software Development AI Platform Ownership

Act as the primary owner and coordinator for AI-assisted software development platforms, including:

• GitHub Copilot
• Claude Code
• Future AI coding assistants and engineering productivity solutions

Responsibilities include:

• Leading rollout and adoption activities
• Defining onboarding processes
• Managing stakeholder engagement
• Driving user adoption and satisfaction
• Supporting operational governance and lifecycle management

Claude Code and Github Copilot Service Delivery and Operations

Own the organizational deployment and lifecycle management of Claude Code.

Key activities:

• Coordinate enterprise rollout of Claude Code
• Manage allocation and reallocation of licenses
• Monitor utilization and consumption
• Ensure licenses are assigned to users generating business value
• Establish governance processes for onboarding, offboarding, and license transfers
• Provide usage insights and recommendations to leadership

Cross-Functional Coordination

Work closely with multiple internal and external stakeholders including:

• ServiceNow teams
• IT Service Portfolio (ITSP)
• Procurement
• Infrastructure teams
• Enterprise Architecture
• Security and Compliance teams
• AI and Software Engineering Communities

Responsibilities include:

• Defining and improving operating processes
• Streamlining request management
• Automating allocation and approval workflows
• Supporting integrations and service improvements
• Ensuring operational alignment across teams

Cost Management and Value Realization

Manage the financial governance of AI engineering tools.

Key activities:

• Establish cost allocation processes
• Support cost center chargeback models
• Track license consumption and utilization
• Provide budgeting inputs and forecasts
• Ensure business value can be traced back to investments
• Support leadership with usage and ROI reporting

Training and Adoption Enablement

Act as the lead enablement resource for AI-assisted software development.

Responsibilities:

• Create and maintain training material
• Conduct user onboarding sessions
• Deliver awareness campaigns and workshops
• Share best practices and success stories
• Support engineering teams in day-to-day adoption

The goal is not only tool deployment but successful adoption and effective usage.

Technology Monitoring and Industry Awareness

Continuously monitor developments in:

• Claude Code
• Anthropic ecosystem
• GitHub Copilot
• Microsoft AI development capabilities
• Open-source coding assistants
• Local and private AI development solutions

Responsibilities include:

• Evaluating newly released features
• Assessing business impact
• Communicating relevant updates to stakeholders
• Recommending improvements to current operating models

Future Technology Exploration

Evaluate alternatives and complementary solutions beyond current tools.

Examples:

• On-premises coding assistants
• Self-hosted AI development platforms
• Secure enterprise LLM solutions
• Open-source development assistants
• Agentic software engineering tools

Responsibilities:

• Conduct proof-of-concept activities
• Develop business cases
• Assess security, compliance, and scalability
• Recommend strategic direction for future engineering productivity platforms

Continuous Improvement

Drive ongoing improvements through:

• User feedback collection
• Adoption metrics
• Productivity measurements
• Cost analysis
• Operational reviews

The role should identify opportunities to optimize tooling, governance, training, and engineering outcomes.

Software Engineering Practices and Development Excellence

Act as a trusted advisor to software engineering teams on how AI-assisted development tools should be integrated into modern software delivery practices.

Responsibilities include:

• Establishing and promoting best practices for effective use of AI-assisted software development tools across the software development lifecycle.
• Coaching development teams on how to use GitHub Copilot, Claude Code, and future AI coding assistants to maximize productivity while maintaining code quality and engineering standards.
• Providing guidance on AI-assisted software design, coding, testing, debugging, refactoring, documentation, and code review practices.
• Defining guardrails and recommended usage patterns to ensure secure, maintainable, and scalable software development.
• Working with engineering leaders, architects, and development teams to identify opportunities for improving developer productivity and delivery effectiveness.
• Supporting teams in adapting software development methodologies and workflows to take advantage of AI-assisted engineering capabilities.
• Staying current with emerging software engineering practices, AI-native development approaches, agentic software engineering concepts, and industry-leading development frameworks.
• Contributing to the definition of engineering standards, reference practices, and recommended ways of working for AI-assisted software development.
• Helping teams measure and improve outcomes related to development productivity, code quality, testing effectiveness, maintainability, and delivery speed.
• Acting as a subject matter expert on how software engineering organizations can evolve from traditional development practices toward AI-augmented and AI-native software delivery models.