Senior Manager - AI Transformation

The role leads cross-functional programs rather than day-to-day DevOps execution, focusing on strategy, alignment, and outcomes across multiple teams and products.\nResponsibilities Program & Strategy Leadership • Owns the E2E AI SDLC program, spanning data ingestion, model development, validation, deployment, monitoring, and continuous improvement.\n• Defines and drives DevX strategy for AI and software delivery, aligning engineering execution with business, security, and compliance objectives.\n• Leads cross-org initiatives to standardize AI SDLC practices, including MLOps, CI/CD for AI, model governance, observability, and release readiness.\n• Translates executive priorities into clear program roadmaps, milestones, and success metrics.\nTechnical Governance & Enablement • Establishes reference architectures, standards, and guardrails for AI-enabled systems across cloud and hybrid environments.\n• Partners with DevOps, MLOps, platform, and security teams to ensure tooling alignment across CI/CD, model lifecycle management, monitoring, and access control.\n• Ensures security, privacy, Responsible AI, and regulatory requirements are embedded into the AI SDLC by design.\n• Evaluates emerging technologies and platforms to recommend scalable, future-ready solutions for AI and developer productivity.\nExecution Oversight (Not Line Execution) • Oversees execution of high-impact, multi-team programs, resolving dependencies, risks, and delivery bottlenecks.\n• Drives adoption of automation, quality gates, and operational readiness criteria for AI and software releases.\n• Establishes program-level dashboards to track health, velocity, compliance, and operational outcomes.\nStakeholder & Leadership Engagement • Acts as the primary point of accountability for AI SDLC maturity across the organization.\n• Provides regular, concise updates to senior leadership on progress, risks, trade-offs, and outcomes.\n• Builds strong partnerships across development, data science, operations, security, legal, and product teams to drive alignment and shared ownership.\nPeople & Capability Development • Leads and mentors program managers, technical leads, and DevX contributors aligned to AI SDLC initiatives.\n• Guides capability development through role-based enablement, best practices, and change management.\n• Influences resourcing and prioritization decisions in collaboration with functional leaders.\nEducation & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, or related discipline, or equivalent practical experience.\n• Typically 10+ years of experience in software engineering, DevOps, platform engineering, AI/ML systems, or large-scale technical program management.\n• 5+ years leading cross-functional technical programs involving multiple engineering and platform teams.\nPreferred Certifications • AWS Certified DevOps Engineer, AWS Machine Learning, Azure AI Engineer, or equivalent cloud/AI certifications.\n• Agile / SAFe Program Consultant (SPC), PMP, or similar program leadership certification (preferred).\nKnowledge & Skills Core Technical • AI/ML Systems & MLOps\n• CI/CD for Software and AI Pipelines\n• Cloud Platforms (AWS, Azure)\n• Automation & Infrastructure as Code\n• Observability, Monitoring, and Model Performance Tracking\n• Microservices & Distributed Systems\n• Security, Compliance, and Access Governance\n• APIs and Platform Integration\nSoftware & AI Development • Python, Java, JavaScript (working knowledge)\n• Containers & Orchestration (Docker, Kubernetes)\n• Data & Model Lifecycle Management\n• Scalability and Reliability Engineering\nProgram & Leadership • Agile & Product-Oriented Delivery Models\n• Dependency & Risk Management\n• Metrics-Driven Execution\n• Executive Communication\n• Change Management\nCross-Org Skills • Strategic Thinking\n• Customer Centricity\n• Prioritization Across Competing Initiatives\n• Resilience in Ambiguous Environments\n• Influence Without Direct Authority\nImpact & Scope • Impacts large, multi-disciplinary engineering and AI functions across HP.\n• Shapes how AI-enabled software is designed, delivered, governed, and operated at scale.\n• Directly influences time-to-market, quality, compliance posture, and developer productivity.\nComplexity • Operates in a highly complex, evolving technical and regulatory landscape.\n• Applies managerial and program leadership concepts to resolve ambiguous, high-impact problems.\n• Achieves outcomes through matrixed teams and indirect leadership.\n\nJob -\nSoftware\nSchedule -\nFull time\nShift -\nNo shift premium (India)\nTravel -\n\nRelocation -\nEqual Opportunity Employer (EEO) -\nHP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).\nPlease be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily.

The information obtained will be kept in strict confidence.\nFor more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "\n]]>