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30 Hours Week Software Developer Jobs in Puerto Rico

Software Developer - Intern

Caguas, PR · On-site

$18.75 - $24.50/hr

Windows 8 Development (.Net) * Some more JavaScript A qualified mobile software developer candidate ... Startup Hours * Startup Energy * Scary Fast Learner * Experience building a well-designed iPhone ...

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30 Hours Week Software Developer information

What is the difference between 30 Hours Week Software Developer vs Full-Time Software Developer?

Aspect30 Hours Week Software DeveloperFull-Time Software Developer
Work HoursApproximately 30 hours per weekTypically 40 hours per week
CredentialsSame as full-time, usually requiring a bachelor's degree in CS or related fieldSame as part-time, usually requiring a bachelor's degree in CS or related field
Work EnvironmentPart-time, flexible schedules, often remote or freelanceFull-time, standard office or remote work
Employer UsageUsed by companies offering flexible or reduced hoursStandard employment model in tech industry

The 30 Hours Week Software Developer typically works fewer hours than a full-time software developer, offering more flexibility. Both roles require similar skills and credentials, but the main difference lies in weekly hours and work schedule. This makes the 30 Hours Week role ideal for those seeking work-life balance or part-time opportunities while maintaining a career in software development.

What is a 30 hours week software developer?

A 30 hours week software developer is a professional who works in software development but has a reduced work schedule, typically working 30 hours per week instead of the traditional 40. This arrangement can provide better work-life balance, flexibility, and can be suitable for those managing other responsibilities or seeking reduced hours. These developers perform the same tasks as full-time developers, such as coding, debugging, and collaborating with teams, but within a shorter workweek.

How does working as a 30 hours per week Software Developer impact team collaboration and project delivery?

As a 30 hours per week Software Developer, you’ll often work in teams that include both full-time and part-time members. Clear communication is essential to ensure smooth collaboration, as your availability may differ from others on the team. Many organizations accommodate flexible schedules by leveraging asynchronous communication tools and setting well-defined expectations for deliverables. While you may need to be proactive about syncing up during overlapping hours, this structure can support a healthy work-life balance without compromising project outcomes.

What are the key skills and qualifications needed to thrive as a 30 Hours Week Software Developer, and why are they important?

To thrive as a 30 Hours Week Software Developer, you need strong programming skills, problem-solving abilities, and a relevant degree or coding bootcamp experience. Familiarity with development tools such as Git, integrated development environments (IDEs), and collaboration platforms like Jira or Slack is typically required. Time management, effective communication, and self-motivation are essential soft skills for success in a reduced-hour, flexible role. These skills ensure that developers can produce high-quality code, meet project goals efficiently, and collaborate well within teams despite a part-time schedule.
What job categories do people searching 30 Hours Week Software Developer jobs in Puerto Rico look for? The top searched job categories for 30 Hours Week Software Developer jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for 30 Hours Week Software Developer jobs? Cities in Puerto Rico with the most 30 Hours Week Software Developer job openings:

$53.50 - $70.50/hr

Full-time

Posted 4 days ago


Job description

Senior 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:
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 will convert architecture into robust implementations, proactively manage risks, and ensure observable, secure, and performant AI systems. Important to have Good Networking knowledge
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 efficacy 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 failure-injection 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.

Education and Experience Required:
  • Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
  • Typically, 7-10 years' experience.

Knowledge and Skills:
  • LLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.
  • ML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE where relevant), 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/queues.
  • Vector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.
  • Ops: GitHub Actions/Azure DevOps, MLFlow/W&B

#LI-Hybrid
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
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We 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.
Unconditional Inclusion
We 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.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
#puertorico
#networking
Job:
Engineering
Job Level:
TCP_04
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 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.
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, including laws requiring employers to consider for employment qualified applicants with criminal histories.
No Fees Notice & Recruitment Fraud Disclaimer
It 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.
Please 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. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.