Key Responsibilities
Develop and integrate AI/GenAI capabilities into software development tools and workflows, including coding, code understanding, code review, testing, debugging, build, CI/CD, and release processes.
Build applications using LLMs, RAG, AI agents, tool calling, MCP, embeddings, and vector databases.
Develop AI-powered assistants and automation that help engineers understand code, diagnose failures, generate tests, analyze defects, and resolve development issues.
Integrate AI capabilities with existing engineering systems, APIs, source-code repositories, CI/CD pipelines, issue tracking, build systems, and developer environments.
Design and implement agentic workflows that can reason over engineering data and take appropriate actions through approved tools and APIs.
Evaluate different models, prompts, agents, and architectures for accuracy, latency, cost, reliability, and developer value.
Develop mechanisms for AI quality evaluation, including automated evaluation, human feedback, regression testing, and monitoring of AI-generated results.
Work with software development teams to understand pain points and translate them into practical AI-powered solutions.
Build scalable, secure, and maintainable AI services suitable for use by large engineering organizations.
Instrument AI applications to measure adoption, productivity impact, quality improvements, and business value.
Participate in design reviews, code reviews, architecture discussions, and engineering best-practice initiatives.
Stay current with rapidly evolving AI technologies and identify opportunities to incorporate relevant advances into internal developer tooling.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field.
2–6 years of software engineering or AI/ML engineering experience, with hands-on experience developing production-quality software.
Practical experience developing applications using Generative AI and Large Language Models (LLMs).
Strong programming skills in Python and/or JavaScript/TypeScript, with good understanding of software engineering principles.
Experience working with LLM APIs, prompt engineering, structured outputs, embeddings, RAG, or agent-based applications.
Experience developing and consuming REST APIs and microservices.
Strong understanding of software development lifecycle, source control, CI/CD, testing, debugging, and engineering workflows.
Familiarity with cloud platforms, containers, Kubernetes, or modern application deployment practices.
Ability to work effectively with software developers and translate engineering problems into practical technical solutions.
Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
Experience building AI agents and multi-step AI workflows.
Experience with MCP, tool/function calling, agent frameworks, or AI orchestration frameworks.
Experience with vector databases, semantic search, knowledge graphs, or RAG architectures.
Experience applying AI to code generation, code review, unit-test generation, code coverage, debugging, build failure analysis, or CI/CD automation.
Familiarity with models from providers such as OpenAI, Anthropic, Google, Meta, or other leading LLM platforms.
Experience with AI evaluation frameworks and techniques for measuring LLM accuracy and reliability.
Knowledge of software engineering productivity metrics and developer experience.
Experience operating AI applications at scale, including observability, cost management, security, and performance optimization.
Key Attributes
Developer-centric: Understands the challenges faced by software engineers and builds solutions that fit naturally into their workflows.
Hands-on: Comfortable moving from an idea or prototype to a production-ready implementation.
AI curious: Continuously experiments with emerging AI capabilities and understands where they can provide meaningful engineering value.
Systems thinker: Able to connect AI capabilities with existing software development infrastructure and enterprise systems.
Outcome-oriented: Focuses on measurable improvements in developer productivity, software quality, and engineering efficiency—not simply AI adoption or model usage.
Collaborative: Works effectively across software development, QA, DevOps, infrastructure, and architecture teams.
What You Will Build
Examples of solutions this role may develop include
AI-powered code understanding and developer assistants
Intelligent code review and code-quality analysis
Automated unit-test and test-case generation
AI-based build and CI/CD failure diagnosis
Intelligent debugging and root-cause analysis
AI-powered software defect and issue analysis
Developer-facing RAG/knowledge assistants
Agentic automation for repetitive software engineering tasks
AI-driven engineering insights and productivity tools
Intelligent automation across the software development lifecycle
Impact
This role provides an opportunity to apply AI at scale to the daily workflows of software engineers. The successful candidate will help create an increasingly AI-enabled software development environment, reducing repetitive engineering work, accelerating development and debugging, improving software quality, and enabling developers to spend more time on higher-value engineering activities.
Relocation support provided to eligible candidates
Accessibility
HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.
Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.
What We Can Offer You
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.
Let's Stay Connected
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Job
- Engineering
- Job Level:
- TCP_03
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
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