Hybrid role in San Juan, PR building AI-powered capabilities for developer workflows. You will design, develop, and deploy Generative AI solutions that aim to improve productivity, quality, and efficiency across software development. Work alongside software engineers, architects, DevOps teams, and engineering leadership to transform how teams code, test, debug, and ship.
What you will build
- 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 and knowledge assistants
- Agentic automation for repetitive software engineering tasks
- AI-driven engineering insights and productivity tools
- Intelligent automation across the software development lifecycle
Responsibilities
- Develop and integrate AI/GenAI capabilities into software development tools and workflows across 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
- Create AI 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 including APIs, source-code repositories, CI/CD pipelines, issue tracking, build systems, and developer environments
- Design and implement agentic workflows that reason over engineering data and take actions via approved tools and APIs
- Evaluate models, prompts, agents, and architectures for accuracy, latency, cost, reliability, and developer value
- Implement AI quality evaluation mechanisms such as automated evaluation, human feedback, regression testing, and monitoring of AI-generated results
- Partner with software development teams to identify pain points and translate them into practical AI-powered solutions
- Build scalable, secure, and maintainable AI services 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
Requirements
- 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, including hands-on production-quality software development
- Practical experience building applications using Generative AI and Large Language Models (LLMs)
- Strong programming skills in Python and/or JavaScript/TypeScript, with solid software engineering fundamentals
- Experience with LLM APIs, prompt engineering, structured outputs, embeddings, RAG, or agent-based applications
- Experience developing and consuming REST APIs and microservices
- Strong understanding of the software development lifecycle, including source control, CI/CD, testing, debugging, and engineering workflows
- Familiarity with cloud platforms, containers, Kubernetes, or modern deployment practices
- Ability to work effectively with developers and translate engineering problems into technical solutions
- Strong analytical, problem-solving, and communication skills
Key technologies you’ll work with
- Generative AI, LLMs, agents, RAG, intelligent automation
- LLM APIs, prompt engineering, structured outputs, embeddings, vector databases
- Tool calling, MCP, embeddings-based systems
- REST APIs, microservices, CI/CD
- Python, JavaScript/TypeScript
- Cloud platforms, containers, Kubernetes
- Source-code repositories, issue tracking, build systems
Benefits and support
- Relocation support provided to eligible candidates
- Health & Wellbeing benefits
- Personal & Professional Development
- Unconditional Inclusion
Accessibility
HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you require accommodation during any stage of the application or interview process, submit your request using the secure form linked in their process. Note: this option is reserved for applicants needing assistance related to a disability.
How you’ll make an impact
Apply AI at scale to the daily workflows of software engineers. The goal is to reduce repetitive engineering work, accelerate development and debugging, improve software quality, and help developers spend more time on higher-value engineering activities.
