Software Engineer II – Generative AI & LLM Platforms

Software Engineer II – Generative AI & LLM 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:
Contributions include applying intermediate level of subject matter expertise to solve common technical problems. Acts as an informed team member providing analysis of information and recommendations for appropriate action. Works independently within an established framework and with moderate supervision.
Role Overview
We are seeking a Junior Software Engineer to support the design, development, testing, and operation of secure and scalable Generative AI products and platforms. In this role, the engineer will work with experienced team members to build foundational skills in large language models (LLMs), retrieval-augmented generation (RAG), vector databases, cloud technologies, networking, and distributed systems. The successful candidate will demonstrate strong programming fundamentals, curiosity, a willingness to learn, and the ability to collaborate effectively while contributing to prototypes, product features, documentation, testing, and production support.
Responsibilities:
Designs limited enhancements, updates, and programming changes for portions and subsystems of systems software, including operating systems, compliers, networking, utilities, databases, and Internet-related tools.
Analyzes design and determines coding, programming, and integration activities required based on specific objectives and established project guidelines.
Executes and writes portions of testing plans, protocols, and documentation for assigned portion of application; identifies and debugs issues with code and suggests changes or improvements.
Participates as a member of project team of other software systems engineers and internal and outsourced development partners to develop reliable, cost effective and high quality solutions for assigned systems portion or subsystem.
Collaborates and communicates with internal and outsourced development partners regarding software systems design status, project progress, and issue resolution.
Education and Experience Required:
Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline.
Typically 2-4 years relevant experience.
Knowledge and Skills:
Foundational software development knowledge gained through academic projects, internships, training, open-source contributions, or equivalent hands-on experience; able to work collaboratively within a team and contribute to clearly defined components of software applications.
Basic proficiency in Python, Golang, or a similar programming language, with an understanding of APIs, testing, debugging, version control, and core software design principles.
Awareness of Generative AI and large language model concepts such as prompts, tokens, embeddings, context, inference, and common limitations, with an interest in developing deeper expertise.
Basic understanding of cloud concepts and services, preferably AWS, including compute, storage, identity and access management, monitoring, and deployment fundamentals.
Foundational networking knowledge, including TCP/IP, routing and switching basics, virtual networks, connectivity, network security, and systematic troubleshooting.
Understanding of fundamental systems concepts such as scalability, reliability, security, performance, data management, and cost awareness.
Ability to receive feedback, ask questions, share knowledge, participate constructively in design and code reviews, and collaborate with experienced engineers.
Curiosity, a learning mindset, and a willingness to experiment with emerging technologies while following established engineering, security, and quality practices.
Ability to work in an agile team, break work into manageable tasks, build simple prototypes, communicate progress, and incorporate feedback into incremental improvements.
Preferred Qualifications
Cloud, Platform, and Network Architecture:
AWS cloud, Kubernetes, infrastructure as code, and CI/CD
Amazon Bedrock and AWS AI/ML services
Amazon EMR, Apache Spark, and Apache Flink
Amazon Aurora PostgreSQL, pgvector, Amazon EKS, and Amazon S3
AI/ML Frameworks and Orchestration:
Hugging Face Transformers and PyTorch
LangChain, LangGraph, and LlamaIndex
MLOps and LLMOps:
Experiment tracking, model registries, and version management
Security, and Compliance:
Privacy-preserving AI and adversarial testing
AI red teaming, content safety, and explainability
What We Can Offer You:
Health & Wellbeing