Senior AI Software Developer

Hewlett Packard Enterprise; San Juan (PR); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Comprehensive benefits for wellbeing

Personal & professional development programs

Job summary

Hewlett Packard Enterprise is seeking a Senior AI Engineer who will own the delivery of AI features, ensuring high code quality and performance.

The role requires 7–10 years of experience, with responsibilities including designing AI systems, building ETL pipelines, and deploying ML models. The position offers a hybrid work environment, allowing for flexibility in working arrangements.

Qualifications

• Typically 7–10 years of professional experience in relevant fields.
• Strong background in AI technologies and data engineering.

Responsibilities

• Own end-to-end delivery of AI features from design to production.
• Translate high-level designs into clear component contracts and service boundaries.
• Implement LLM integrations, maintain high code quality and documentation.
• Build ETL pipelines and enforce data governance.
• Containerize workloads and own CI/CD for ML.

Skills

Prompt engineering

Containerization (Docker)

Kubernetes

Python (FastAPI/Flask)

ML/DS evaluation metrics

CI/CD

Education

Bachelor’s or master’s in computer science or related

Tools

PyTorch

TensorFlow

SQL

GitHub Actions

Job description

This role is 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 a global edge‑to‑cloud company that helps businesses connect, protect, analyze, and act on their data and applications wherever they live. Our culture values diverse backgrounds, flexibility, and bold innovation.

Job Description

The Senior AI Engineer owns end‑to‑end delivery of AI features—from design to production—while raising the engineering bar through code quality, reliability, and mentoring. The engineer converts architecture into robust implementations, proactively manages risks, and ensures observable, secure, and performant AI systems.

Responsibilities

Solution Engineering & Delivery

• Translate high‑level designs into clear component contracts, APIs, and service boundaries.
• Implement LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.
• Own feature delivery for sprints/releases; maintain high code quality and documentation.

Modeling & Evaluation

• Fine‑tune models when needed; design evaluation harnesses and metrics.
• Build A/B testing setups; track accuracy, latency, robustness, and task success rates.
• Conduct error analysis; iterate using feedback loops and prompt refinement.

Data & Retrieval Engineering

• Build ETL/ELT pipelines; curate datasets with metadata, lineage, and validation.
• Implement vector indexing (chunking, embeddings, reranking); tune chunk size & overlap.
• Enforce data governance: PII handling, redaction, consent, auditability.

MLOps & Platform Readiness

• Containerize workloads (Docker); orchestrate deployments (Kubernetes/Helm).
• Own CI/CD for ML: train → evaluate → package → deploy → monitor → rollback.
• Maintain model/agent registries, experiment tracking, and reproducible environments.

Software Engineering & Integration

• Build microservices and async inference paths; support batch/stream processing.
• Integrate with enterprise auth, observability, telemetry, and logging.
• Write unit/integration/e2e tests, performance benchmarks, and reliability tests.

Observability, Reliability & Performance

• Instrument with metrics, logs, traces; define SLOs (latency, throughput, error rate).
• Optimize inference: batching, caching (KV cache), quantization, token efficiency.
• Implement guardrails (safety filters, jailbreak detection), auto‑evals and alerts.

Security & Compliance

• Apply secure coding practices; manage secrets, encryption, and least privilege.
• Ensure compliance (data residency, consent, audit trails); respect IP policies.
• Enforce policy‑based access and content safety in user‑fac­ing features.

Collaboration & Mentoring

• Review designs/PRs; coach L3 engineers on best practices.
• Coordinate with AI Architects, Data Engineers, QA, and Product teams.

Education And Experience Required

• Bachelor’s or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline.
• Typically 7–10 years of professional experience.

Knowledge And Skills

• LLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.
• ML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE), error analysis.
• Data/RAG: Embeddings, similarity (cosine/IP), chunking, rerankers, vector DB operations.
• Backend: Python (FastAPI/Flask), microservices patterns.
• MLOps/Infra: Docker, Kubernetes, CI/CD, artifact management, GPU scheduling.
• Observability: Metrics, logging, tracing, dashboards, automated evaluation pipelines.
• Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex.
• Data: Pandas, SQL/NoSQL, Parquet/Arrow, Kafka or queues.
• Vector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.
• Ops: GitHub Actions or Azure DevOps, MLflow, WandB.

Additional Skills

• Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security‑First Mindset.

What We Can Offer You

Health & Wellbeing

A comprehensive suite of benefits that supports physical, financial, and emotional wellbeing for team members and their loved ones.

Personal & Professional Development

Programs to help you reach career goals, whether advancing inside your field or exploring new divisions.

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 are based on qualifications, merit, and business need. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran / Individual with Disabilities. HPE will comply with all applicable laws related to employer use of arrest and conviction records.