Description
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.
We're hiring a technical lead for the AI Enablement team. As a tech lead, you'll independently drive high-impact 'lighthouse' AI use cases from concept through production: owning the technical direction, partnering across functions and business units to deliver value, and establishing scalable architectures, patterns, and standards that make each subsequent use case faster and more effective.
Key Responsibilities
- Lead lighthouse use cases end-to-end. Independently own selected high-impact AI use cases from problem framing and solution design through production deployment and the transition to operational ownership, bringing LLM, agentic, and applied AI approaches to bear where they fit.
- Build for production and measurable impact. Design the architecture of AI systems for scalability, performance, reliability, security, and supportability. Establish evaluation, guardrails, monitoring, documentation, and performance metrics that enable trusted adoption in real workflows, and continuously improve the systems based on operational feedback.
- Create reusable patterns. Turn each delivery into reference architectures, tooling, and repeatable patterns that lower the cost of the next use case, so the team scales through leverage, not headcount.
- Partner across the organization. Work closely with stakeholders across business units, product, engineering, data, security, and HPE Labs to translate customer requirements, business needs, and industry trends into AI products, solutions, and systems improvements.
- Provide technical leadership and mentorship. Serve as a recognized technical authority for significant AI initiatives, guide architecture and design reviews across projects, promote consistency and engineering best practices, and coach less-experienced engineers through code review, design review, pairing, and example.
Preferred Qualifications
- Typically, 10+ years of relevant experience in applied AI/ML engineering, or software engineering, including hands-on delivery of AI/ML systems into production.
- Demonstrated ability to take an AI/ML solution from concept to production independently, not just modeling, but the full lifecycle: data pipelines, deployment, evaluation, and operationalization.
- Demonstrated experience shipping an LLM or agentic system that real users depend on, with ownership of its evaluation, reliability, and operation after launch.
- Experience building and scaling enterprise agentic AI solutions across complex, production-grade environments.
- Strong, current depth across AI and machine learning, including supervised and unsupervised learning, deep learning, natural language processing, large language models, generative AI, agentic systems, and statistical modeling, with practical experience in LLMOps or MLOps, evaluation, and production model lifecycle management.
Benefits
- Health & Wellbeing: We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial, and emotional wellbeing.
- Personal & Professional Development: We also invest in your career because the better you are, the better we all are.
- Unconditional Inclusion: We are unconditionally inclusive in the way we work and celebrate individual uniqueness.