Principal Innovation Developer – Cloud & AI

About the role

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 value diverse backgrounds and succeed together, with flexibility to manage work and personal needs.

As an Innovation Engineer in the Hybrid Cloud CTO organization, you will play a senior individual contributor role responsible for driving complex, high-impact incubation projects across AI, cloud-native architectures, and emerging software technologies. Working alongside technical leads and cross-functional partners, you will design, implement, and validate advanced solutions that accelerate HPE's transformation and deliver innovative capabilities to internal teams and external customers. You will apply deep expertise in distributed systems, Generative AI, microservices, and cloud technologies to create robust, scalable, and secure services. This role demands the ability to blend hands‑on development with architectural leadership, proactively generate and advance innovative concepts, and uphold technical excellence across a diverse portfolio of projects.

Responsibilities

• Serve as a senior technical contributor on complex AI and cloud-native incubation projects, owning design and implementation of key components.
• Lead teams of up to 5-6 engineers of multiple disciplines through the full lifecycle of concept development while collaborating with multiple stakeholders.
• Evaluate and integrate emerging software technologies, including Generative AI frameworks (LLMs, RAG, LangGraph, Knowledge Graphs, ADK, A2A).
• Design, build, and validate microservices and cloud-native systems deployed across public cloud, datacenter, and edge environments.
• Contribute to technical architecture decisions, ensuring solutions meet requirements for scale, performance, security, and reliability.
• Collaborate closely with internal customers, technical leads, and business stakeholders to align emerging technologies with strategic objectives.
• Conduct research spikes, proofs-of-concept, and experiments that evaluate feasibility and technical trade-offs.
• Implement high-quality code following best practices in AI assisted code generation (GitHub CoPilot), testing, validation, CI/CD, and observability.
• Provide mentorship and knowledge-sharing to team members of all levels on advanced software and AI topics.
• Work effectively across multiple parallel projects in a dynamic environment with frequent context switching.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, AI/ML, or related technical field.
• Typically 10-15 years of software development experience, with at least 3-5 years focused on cloud-native and AI/ML systems.

Skills

• Strong programming proficiency in Python and experience with ML libraries (PyTorch, TensorFlow, Transformers).
• Deep understanding of distributed systems, microservices, and event-driven architectures.
• Hands-on experience with Kubernetes, Docker, REST APIs, and cloud-native application development.
• Experience implementing Generative AI solutions using LLMs, RAG, LangGraph, or similar frameworks.
• Working knowledge of multiple technologies to include vector databases, graph, NoSQL and RDBMS systems.
• Experience deploying cloud solutions on AWS, Azure, or GCP.
• Strong understanding of AI Governance and Security alignment, and responsible AI principles.
• Proficiency in Agile development methodologies, including Scrum or Kanban.
• Experience contributing to large-scale cloud service development environments.

Preferred qualifications

• Experience with multi-agent systems and agent orchestration frameworks.
• Knowledge of Model Context Protocol (MCP) server development.
• Understanding of Google ADK and A2A protocol implementations.
• Knowledge graph design, construction, and querying.
• Familiarity with ML Ops tools (MLflow, Weights & Biases, LangSmith).
• Experience with observability platforms like Prometheus, Grafana, or OpenTelemetry.

Benefits

• Health & Wellbeing: Comprehensive suite of benefits supporting physical, financial and emotional wellbeing for team members and their loved ones.
• Personal & Professional Development: Investment in career growth with programs catered to helping reach career goals, whether becoming a knowledge expert or applying skills to another division.
• Unconditional Inclusion: Inclusive work culture celebrating individual uniqueness, with flexibility to manage work and personal needs.

Pay

Annual base salary ranges (USD) by location:

• Colorado: $165,500 - $313,500
• Massachusetts: $178,000 - $339,000
• North Carolina & Texas: $157,000 - $361,000

Variable incentives may also be offered. Additional benefits information available at myhperewards.com.

Schedule

Hybrid role with expectation to work on average 2-3 days per week from an HPE office.