Project Manager

Assignment Description 1. 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 2. 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 3. 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 4. 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 5. 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. 6. 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 7. 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 8. 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. 9. 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 within Husqvarna Group. · 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.