Software Engineering Manager – Generative AI & Enterprise Platforms
Hewlett Packard Enterprise
- Location
- San Juan, Puerto Rico, Puerto Rico
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 167 approvals (FY2023)
- Posted
- Aug 28, 2026
Skills
About this role
Software Engineering Manager – Generative AI & Enterprise Platforms This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.
Who We Are
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description
Job Family Definition: Designs, develops, troubleshoots and debugs software programs for software enhancements and new products. Develops software including operating systems, compilers, routers, networks, utilities, databases and Internet-related tools. Determines hardware compatibility and/or influences hardware design. Management Level Definition: Applies advanced subject matter knowledge to manage staff activities in solving common and complex business/technical issues within established policies. Manages exempt individual contributors and/or supervisors. Has accountability for results of a major program in terms of cost, direction and people management. Provides guidance on process improvements and recommends changes in alignment with business tactics and strategy for area of responsibility. Plans, manages and monitors operational/tactical activities of Staff. Staff members' work may involve strategic issues. Recruits and supports development of direct staff members. Typically reports to MG2 or Director. Additional guidance/criteria: Manages and controls activities within a single country or a sub-region which is part of a larger geographical Region; Manages at least 4 employees and typically between 8 and 15 direct reports. Span of Control guidelines may differ from these numbers. We are seeking a Software Engineering Manager to lead a multidisciplinary team building secure, scalable enterprise products powered by Generative AI and large language models. The team includes principal and senior engineers across AI platforms, model customization, React-based generative user experiences, AWS cloud and networking, and quality engineering. This role combines people leadership, delivery ownership, technical judgment, and organizational influence. The successful candidate will develop engineers, establish an inclusive and high-accountability culture, align execution with product strategy, and guide rapid experimentation through production-scale delivery Responsibilities: People and organizational leadership: Build, coach, retain, and grow an inclusive, accountable multidisciplinary engineering team with clear ownership and succession planning. Requirements and delivery management: Translate customer and product needs into clear outcomes, roadmaps, staffing plans, milestones, dependencies, acceptance criteria, and incremental releases. Agile execution and adaptability: Enable rapid feedback, disciplined prioritization, risk management, transparent reporting, and effective re-planning as requirements and priorities evolve. Innovation and productization: Support fast experimentation and proofs of concept, then transition validated ideas into secure, maintainable, production-ready products. Technical direction and engineering standards: Partner with senior technical leaders to guide architecture and establish expectations for quality, security, accessibility, responsible AI, testing, observability, CI/CD, documentation, and technical debt. Quality, security, and operational excellence: Ensure strong AI and software