AI Engineer – Software Development Tools

AI Engineer – Software Development Tools

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:

Position Overview

We are seeking a Junior-to-mid-level AI Engineer to design, develop, and deploy AI-powered solutions that improve the productivity, quality, and efficiency of software development across the company. This role will work closely with software engineers, architects, DevOps teams, and engineering leadership to identify high-value developer workflows and transform them using Generative AI, LLMs, agents, RAG, and intelligent automation .

The engineer will contribute across the full lifecycle—from identifying opportunities and prototyping AI solutions to integrating them into existing software development tools and workflows. The ideal candidate combines strong software engineering fundamentals with practical experience building AI/LLM applications and a passion for improving the developer experience.

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

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