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Agentic SDLC Project Manager

The Agentic SDLC Project Manager leads the internal program to design, build and scale AI agents across the software development lifecycle. The role turns the Agentic Engineering vision into an executable roadmap and aligns product, engineering, AI and business stakeholders to deliver enterprise-ready capabilities and measurable value.

  • Germany
  • Posted Nov 12, 2026
INDUSTRYSoftware & InternetSaaS & Enterprise SoftwareAI & Machine LearningDeveloper Tools & Infrastructure

Responsibilities

  • Own the Agentic SDLC roadmap and delivery lifecycle, from use-case discovery and prioritization through design, build, validation, rollout and scaling.
  • Manage the portfolio of AI agents across requirements, development, code review, testing, release, deployment and operations.
  • Partner with Product and Engineering leaders to define capabilities, user journeys, acceptance criteria, backlog priorities and target outcomes.
  • Coordinate cross-functional teams across AI, application development, data, architecture, QA, DevOps, security, privacy and platform engineering.
  • Manage plans, resources, vendors, environments, integrations, risks and dependencies across parallel workstreams.
  • Establish governance and quality gates covering human oversight, security, responsible AI, traceability and production readiness.
  • Drive pilots, adoption and stakeholder communication, using feedback and delivery insights to improve the roadmap and reusable patterns.

Requirements

  • Bachelor's degree in Information Systems, Computer Science, Engineering or a related field
  • Experience in a Software development
  • Experience in a AI
  • Experience in a Data
  • Experience in a Automation
  • Experience in a Digital products

Nice to have: Microsoft Copilot Studio, Azure AI Foundry, GitHub Copilot, Microsoft Power Platform, Azure DevOps, Confluence, GitHub, AI evaluation, Data and AI governance, Responsible AI, Security, Privacy, Validation

Skills

Generative AIAI agentsAgentic workflowsOrchestrationTool integrationEvaluationHuman oversightProduct managementRoadmap definitionBacklog prioritizationEnd-to-end SDLC processesJiraAzure DevOpsConfluenceGitHub

Full description

Description The Agentic SDLC Project Manager leads the internal program to design, build and scale AI agents across the software development lifecycle. The role turns the Agentic Engineering vision into an executable roadmap and aligns product, engineering, AI and business stakeholders to deliver enterprise-ready capabilities and measurable value. Key responsibilities: Own the Agentic SDLC roadmap and delivery lifecycle, from use-case discovery and prioritization through design, build, validation, rollout and scaling. Manage the portfolio of AI agents across requirements, development, code review, testing, release, deployment and operations. Partner with Product and Engineering leaders to define capabilities, user journeys, acceptance criteria, backlog priorities and target outcomes. Coordinate cross-functional teams across AI, application development, data, architecture, QA, DevOps, security, privacy and platform engineering. Manage plans, resources, vendors, environments, integrations, risks and dependencies across parallel workstreams. Establish governance and quality gates covering human oversight, security, responsible AI, traceability and production readiness. Drive pilots, adoption and stakeholder communication, using feedback and delivery insights to improve the roadmap and reusable patterns. Requirements Must-have skills & experience: 5+ years managing complex technology projects or programs involving software development, AI, data, automation or digital products. Working knowledge of generative AI, AI agents and agentic workflows, including orchestration, tool integration, evaluation and human oversight. Product management or product delivery experience, including discovery, roadmap definition, backlog prioritization and outcome measurement. Expert-level Jira proficiency, including workflow and board configuration, backlog and release management, dashboards, automation and delivery metrics. Deep understanding of end-to-end SDLC processes, roles, controls and engineering practices. Proven ability to lead global, cross-functional teams and manage scope, resources, risks, dependencies, vendors and senior stakeholder expectations. Strong command of Agile and hybrid delivery methods, with excellent analytical, facilitation, negotiation and problem-solving skills. Nice to have: Hands-on experience delivering AI agents, copilots, developer productivity solutions or intelligent automation. Experience with Microsoft Copilot Studio, Azure AI Foundry, GitHub Copilot or Microsoft Power Platform. Proficiency with Azure DevOps, Confluence, GitHub or comparable product and engineering delivery tools. Experience with AI evaluation, data and AI governance, responsible AI, security, privacy, validation or regulated environments. Project management, product management or Agile certification, such as PMP, PRINCE2, CSPO, CSM, PSM or SAFe. Bachelor's degree in Information Systems, Computer Science, Engineering or a related field.

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