HPE
Principal Innovation Developer – Cloud & AI
$157K–$361K
Andover, Massachusetts, United States of America +3 · Principal · Full-time · Posted Oct 19, 2026
- Location
- Andover, Massachusetts, United States of America
Ft. Collins, Colorado, United States of America
Durham, North Carolina, United States of America
Spring, Texas, United States of America - Experience
- Typically 10–15 years of software development experience, including at least 3–5 years focused on cloud-native and AI/ML systems.
- Education
- Bachelor’s or Master’s degree in Computer Science, Information Systems, AI/ML, or related technical field.
About the job
Leads hands-on incubation projects that develop and validate scalable AI and cloud-native solutions for HPE and its customers.
What you'll do
- Own design and implementation of key components for complex AI and cloud-native projects; guide teams of up to 5–6 engineers.
- Build and validate microservices and cloud-native systems across public cloud, datacenter, and edge environments, while contributing to architecture decisions.
- Evaluate emerging technologies through research, proofs of concept, and experiments; collaborate with stakeholders and mentor engineers.
What they ask for
- Bachelor’s or Master’s degree in Computer Science, Information Systems, AI/ML, or a related technical field.
- Strong Python skills and experience with ML libraries such as PyTorch, TensorFlow, or Transformers.
- Experience with distributed systems, microservices, Kubernetes, Docker, REST APIs, and cloud-native development.
- Experience implementing Generative AI solutions and deploying cloud solutions on AWS, Azure, or GCP.
Nice to have
- Experience with multi-agent systems, agent orchestration, MCP, Google ADK, or A2A.
- Familiarity with ML Ops tools or observability platforms, and knowledge graph design.
Pay
USD 165,500 - 313,500 in Colorado (base salary); USD 178,000 - 339,000 in Massachusetts (base salary); USD 157,000 - 361,000 in North Carolina & Texas (base salary)
Tools
Python, PyTorch, TensorFlow, Transformers, Kubernetes, Docker, AWS, Azure
AI focus
Develops and evaluates Generative AI and AI/ML solutions, including LLM and RAG frameworks; addresses AI governance, security, and responsible AI.
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