AI Software Developer

AI Software Developer

This role has been designed as 'Hybrid' with an expectation 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:

We are seeking for a Full‑Stack Engineer as an individual contributor who delivers well-scoped tasks across the Application, follows established patterns, and steadily builds proficiency in testing, performance, and security. They work closely with more senior engineers, demonstrating reliability, learning agility, and ownership of modules assigned within a sprint.

Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects.

Responsibilities:

Feature Implementation (UI + API)

* Builds UI components and pages using established design systems and patterns.

* Implements backend endpoints (CRUD, pagination, filters) and basic business logic.

* Maintains clean API contracts: request/response types, error structures, and HTTP status codes.

Data & Integration

* Wire up state management and data fetching; handle retries and error states.

* Integrate authentication/authorization flows and basic role checks.

* Consume internal/external services (e.g., LLM endpoints, orchestration APIs) under guidance.

Quality & Testing Hygiene

* Write unit and integration tests for UI and backend modules.

* Add validation, error handling, and logging hooks for observability.

* Follow linting, type safety, and code style guidelines; keep docs up to date.

Performance & Reliability Basics

* Optimize UI rendering (memoization, keying), reduce bundle bloat (tree-shaking).

* Avoid N+1 queries, use indexes where applicable, and apply simple caching patterns.

* Participate in bug triage; provide clear repro steps and fix prioritization with guidance.

Dev Ops & CI/CD Fundamentals

* Contribute to build pipelines (tests, static checks), environment variables, and configs.

* Containerize services using Docker; understand image layering and .dockerignore basics.

* Use feature flags safely; handle secrets via managed mechanisms (never hard-code).

Collaboration & Communication

* Work with designers, product, QA/SRE, and senior engineers; seek clarifications early.

* Share status succinctly; document decisions and assumptions in ADRs/design notes.

Education and Experience

Required:

* Bachelor's degree in computer science, engineering, data science or closely related quantitative discipline.

* Typically, 2-4 years' experience.

Knowledge and

Skills:

* Frameworks:
React (preferred) / Angular ; modern hooks/patterns.

* UI/UX: HTML5, CSS3/Sass, Tailwind/Material; accessibility (a11y), responsive design.

* Languages/Frameworks:
Python (FastAPI/Flask) or Node.js (Express/NestJS);

* APIs: REST/gRPC; pagination, filtering, versioning, OpenAPI/Swagger.

* Data: SQL (Postgres/MySQL) and No

SQL (Mongo/Redis); ORMs (SQL Alchemy/Prisma).

* Testing: pytest/Jest; integration and contract tests.

* Containers:
Docker basics; compose; image optimization.

* CI/CD:
Git Hub Actions/Azure Dev Ops; pipelines, artifacts, environments.

* Cloud:
Familiarity with cloud services (AWS/Azure/GCP) and environments.

* Observability:
Logs/metrics/traces; dashboarding; alerting fundamentals.

* AI‑Integration (Nice‑to‑Have for AI Apps)

* Consume LLM/agent APIs; handle token/latency/cost controls.

* Work with RAG services (vector search endpoints); understand request/response patterns.

* Implement prompt/response logging and guardrails integration (basic filters).

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