AI Software Developer

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. DevOps & 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.