Principal Engineer - AI/ML

Principal Engineer - AI/ML

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Job Description:

In the HPE Hybrid Cloud, we lead the innovation agenda and technology roadmap for all of HPE. This includes managing the design, development, and product portfolio of our next-generation cloud platform, Green Lake. Working with customers, we help them reimagine their information technology needs to deliver a simple, consumable solution that helps them drive their business results. Join us redefine what’s next for you.

Principal Generative AI Engineer

As a Principal Generative AI Engineer,  you will be responsible for driving the roadmap and building the next generation Generative AI Platform and GenAI Models/Algorithms that our userbase will leverage for years to come as we scale our efforts to implement GenAI in our Product. You should be comfortable with petabytes of data, writing crisp design documentation, and building, debugging, and maintaining highly available distributed systems. The GenAI platforms that you build will empower developers throughout HPE to build better AI products more quickly than ever before. You will be at the forefront of development, research, and implementation of innovative GenAI models, prompting strategies, agentic AI systems, and pipelines.

The ideal candidate should have a strong background in applied generative AI approaches, large language models, multimodal AI, agentic AI, and production-level engineering. You should have excellent problem solving and communication skills, and be comfortable working with data scientists, product managers, and other engineers. You should have a passion for creating GenAI products and be able to think through the implications of the solutions you create. A successful candidate should have an advanced degree in computer science, mathematics, engineering, or a related field, and have a strong portfolio of GenAI/LLM projects.

You should design and build highly scalable systems, generative AI algorithms, and deep learning applications. You should be able to execute tests and optimize GenAI models and prompt/agentic workflows. You should also be able to mentor and guide other GenAI Engineers in the team.

What you will do:

• Experiment, design, develop and maintain generative AI models (e.g., LLMs, multimodal models), agentic AI architectures, and pipelines with high potential for value and scale.
• Collaborate with other GenAI engineers, data scientists, product managers, and other engineers to ensure successful implementation of generative AI solutions.
• Perform research and testing to develop or customize GenAI algorithms, prompt engineering strategies, and agentic workflows; conduct model training, fine-tuning, and evaluation as needed; integrate, test, tune and monitor the solutions developed.
• Research and evaluate new technologies and tools for generative AI, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic AI frameworks, model evaluation and safety tools.
• Maintain and update existing generative AI systems, including prompt libraries, agent workflows, and deployed models.
• Troubleshoot and debug GenAI systems, including issues related to model outputs, prompt reliability, hallucinations, and agentic behaviors.
• Work collaboratively with cross-functional partners and stakeholders, identify opportunities for business impact, understand, refine, and prioritize requirements for GenAI models and solutions, drive engineering decisions, and quantify impact.
• Hands-on development, productionization, and operation of GenAI models, agents, and pipelines at scale, including both batch and real-time use cases.
• Work with large scale structured and unstructured data, build and continuously improve cutting edge GenAI models, including LLMs, vision-language models, and agentic systems.
• Provide technical guidance and mentorship to other team members and interns in GenAI best practices, prompting strategies, and agentic design.
• Identify areas of improvement in existing GenAI systems, including prompt engineering, agent reliability, and model deployment.

What you will need:

• B.E/B.Tech/M.Tech/M.E degree in Computer Science or equivalent
• 10-12 years of industry experience in applied AI/GenAI, designing and developing scalable enterprise level solutions
• Experience in architecting and building large, highly scalable systems & software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, agentic workflows, prompt orchestration)
• Strong programming (Python / C++ or equivalent) and data engineering skills
• Deep understanding of Generative AI best practices (e.g., prompt engineering, RAG, agentic design, model fine-tuning, optimization), LLMs, multimodal models, and deep learning basics.
• Experience with these technologies: OpenAI GPT, Llama, Hugging Face Transformers, LangChain, DeepSpeed, Ray, Kubernetes, Spark, Kafka (or equivalent).
• Industry experience building end-to-end GenAI infrastructure and/or building and productionizing Generative AI models, agents, and workflows
• Experience with MLOps/LLMOps practices and tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI)
• Design, implement and integrate the next generation of Generative AI infrastructure to empower other Data Scientists and AI engineers to build GenAI models and agents that make real-time decisions.
• You will collaborate with other engineers and data scientists to create optimal experiences on the Core GenAI platform, including but not limited to: prompt libraries, agentic orchestration, the real-time serving layer, and the offline training system
• Strong collaboration and communication skills, both verbal and written
• Bring a deep empathy for customer needs and insights as well as an intuitive grasp of the business problems we’re trying to solve

Good to have:

• Experience with traditional machine learning and deep learning frameworks and algorithms (e.g., RNNs, CNNs, Transformers, GANs)
• Knowledge of reinforcement learning, transfer learning, and meta-learning concepts
• Hands-on experience with TensorFlow, PyTorch, JAX, Keras
• Familiarity with data labeling platforms, ML model monitoring and evaluation tools
• Experience with MLOps/LLMOps practices and tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI)
• Exposure to model safety, bias detection, explainability, and responsible AI practices
• Experience with cloud platforms (AWS, Azure, GCP) for scalable AI deployments
• Contributions to open source GenAI/ML projects or research publications

Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX)

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. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

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Job:

Engineering

Job Level:

TCP_05

    

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.