{"id":1172639,"url":"https://alion.io/job/hewlett-packard-enterprise-senior-ai-software-developer","title":"Senior AI Software Developer","company":{"id":5292,"name":"Hewlett Packard Enterprise","domain":"hpe.com","url":"https://alion.io/company/hewlett-packard-enterprise","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":122,"ghost_share":0,"stale_share":0.811,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Juan, Puerto Rico","Puerto Rico"],"countries":["PR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":96000,"max_usd":249000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2216},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Helm","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"KV Cache","optional":false},{"name":"LangChain","optional":false},{"name":"Least Privilege","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"MLFlow","optional":false},{"name":"Pandas","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weaviate","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Azure","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-02-19T00:00:00Z","employer_posted_date":"2026-02-19","last_verified_at":"2026-10-22T10:16:30Z","board_verified":true,"closed_at":null,"days_open":245,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":245},"description":"Senior AI Software DeveloperThis 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:\nHewlett 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.\nJob Description:\nThe 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 will convert architecture into robust implementations, proactively manage risks, and ensure observable, secure, and performant AI systems. Important to have Good Networking knowledge\nResponsibilities:\nSolution Engineering & Delivery\nTranslate high-level designs into clear component contracts, APIs, and service boundaries.\nImplement LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.\nOwn feature delivery for sprints/releases; maintain high code quality and documentation.\nModeling & Evaluation\nFine-tune models when needed; design evaluation harnesses and metrics.\nBuild A/B testing setups; track accuracy, latency, robustness, and task success rates.\nConduct error analysis; iterate using feedback efficacy loops and prompt refinement.\nData & Retrieval Engineering\nBuild ETL/ELT pipelines; curate datasets with metadata, lineage, and validation.\nImplement vector indexing (chunking, embeddings, reranking), tune chunk size & overlap.\nEnforce data governance: PII handling, redaction, consent, auditability.\nMLOps & Platform Readiness\nContainerize workloads (Docker); orchestrate deployments (Kubernetes/Helm).\nOwn CI/CD for ML: train → evaluate → package → deploy → monitor → rollback.\nMaintain model/agent registries, experiment tracking, and reproducible environments.\nSoftware Engineering & Integration\nBuild microservices and async inference paths; support batch/stream processing.\nIntegrate with enterprise auth, observability, telemetry, and logging.\nWrite unit/integration/e2e tests, performance benchmarks, and failure-injection tests.\nObservability, Reliability & Performance\nInstrument with metrics/logs/traces; define SLOs (latency, throughput, error rate).\nOptimize inference: batching, caching (KV cache), quantization, token efficiency.\nImplement guardrails (safety filters, jailbreak detection), auto-evals and alerts.\nSecurity & Compliance\nApply secure coding practices; manage secrets, encryption, and least privilege.\nEnsure compliance (data residency, consent, audit trails); respect IP policies.\nEnforce policy-based access and content safety in user-facing features.\nCollaboration & Mentoring\nReview designs/PRs; coach L3 engineers on best practices.\nCoordinate with AI Architects, Data Engineers, QA, and Product.\nEducation and Experience Required:\nBachelor's or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.\nTypically, 7-10 years’ experience.\nKnowledge and Skills:\nLLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.\nML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE where relevant), error analysis.\nData/RAG: Embeddings, similarity (cosine/IP), chunking, rerankers, vector DB operations.\n Backend: Python (FastAPI/Flask), microservices patterns.\nMLOps/Infra: Docker, Kubernetes, CI/CD, artifact management, GPU scheduling.\nObservability: Metrics/logging/tracing, dashboards, automated evaluation pipelines.\nFrameworks: PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.\nData: Pandas, SQL/NoSQL, Parquet/Arrow, Kafka/queues.\nVector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.\nOps: GitHub Actions/Azure DevOps, MLFlow/W&B\nAdditional Skills:\nArtificial 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 MindsetWhat We Can Offer You:\nHealth & Wellbeing\nWe strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.\nPersonal & Professional Development\nWe also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.\nUnconditional Inclusion\nWe are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.\nLet's Stay Connected:\nFollow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.\n#puertorico#networkingJob:\nEngineeringJob Level:\nTCP_04HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBTemployer. We do not discriminate on the basis of race, gender, or any other protected category,and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.\nHewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.\nHPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.\nNo Fees Notice & Recruitment Fraud Disclaimer\nIt has come to HPE’s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates. These scammers often seek to obtain personal information or money from candidates.\nPlease note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. 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