Unit4 is hiring an AI Strategy & Adoption Lead

Role Responsibilities: - Define and execute the AI adoption roadmap for software development. - Identify and validate high-value AI use cases, including agentic development scenarios. - Select and onboard appropriate AI tools and platforms. - Coordinate pilots, measure outcomes, and scale successful initiatives. - Establish best practices, standards, and governance for AI usage in development. - Educate and support development teams in leveraging AI effectively. Kwalifikacje: - Proven experience in designing and implementing AI-driven solutions within software development environments (e.g., AI-assisted coding, testing automation, DevOps optimization). - Strong understanding of the software development lifecycle (SDLC) and ability to identify high-impact areas for AI enablement. - Hands-on experience with LLMs, GenAI, and agentic workflows (e.g., AI agents for code generation, test creation, documentation, or release automation). - Ability to define, lead, and coordinate AI adoption processes, from strategy through pilot execution to scaled rollout. - Experience in evaluating and selecting AI tools and platforms (e.g., Copilot, code assistants, AI testing tools, orchestration frameworks), including cost–benefit and ROI analysis. - Strong analytical skills to identify and prioritize use cases with the highest business value (e.g., agentic development candidates, automation opportunities). - Experience with integration of AI solutions into existing development ecosystems (e.g., Azure DevOps, CI/CD pipelines, code repositories). - Familiarity with data architecture concepts, including RAG, embeddings, vector databases, and knowledge grounding. - Understanding of software quality, security, and compliance considerations (e.g., code quality, GDPR, secure AI usage). - Ability to work across technical and business domains, translating needs into practical AI implementation plans. - Strong stakeholder management and communication skills, with experience driving cross-functional initiatives. Nice to Have: - Experience with AI governance frameworks and responsible AI practices. - Background in agent-based architectures and orchestration tools (e.g., LangChain, Semantic Kernel, AutoGen). - Knowledge of test automation frameworks and AI-driven QA (e.g., E2E, synthetic data, test generation). - Experience in change management and AI adoption within enterprise organizations.