Senior AI Software Developer (AI)

Location: Hybrid, with an expectation of working an average of 2 days per week from an HPE office in San Juan or Aguadilla, Puerto Rico.

Company

hirify.global is a global edge-to-cloud technology company developing solutions that connect, protect, analyze, and act on data and applications.

What you will do

• Translate architecture into component contracts, APIs, service boundaries, robust implementations, and documented production features.
• Build LLM integrations, RAG pipelines, agents, tool and function calling, prompt strategies, ETL/ELT pipelines, datasets, vector indexing, and retrieval systems.
• Design model fine-tuning, evaluation harnesses, metrics, A/B tests, error analysis, feedback loops, and automated evaluations.
• Containerize and deploy AI workloads with Docker, Kubernetes, and Helm; own the ML CI/CD lifecycle from training and evaluation through deployment, monitoring, and rollback.
• Develop microservices, asynchronous inference paths, batch and stream processing, enterprise integrations, tests, observability, SLOs, performance optimizations, and reliability controls.
• Apply secure coding, data governance, privacy, consent, auditability, access control, content safety, and compliance practices; review designs and code and mentor L3 engineers.

Requirements

• 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 experience.
• Knowledge of LLMs and agents, including prompt engineering, function and tool calling, orchestration frameworks, and RAG.
• Knowledge of evaluation metrics such as precision/recall and BLEU/ROUGE where relevant, plus error analysis.
• Experience with embeddings, cosine/IP similarity, chunking, rerankers, and vector database operations.
• Backend Python development with FastAPI or Flask and microservices patterns.
• MLOps and infrastructure knowledge, including Docker, Kubernetes, CI/CD, artifact management, and GPU scheduling.
• Experience with metrics, logging, tracing, dashboards, and automated evaluation pipelines.
• Knowledge of PyTorch or TensorFlow, Hugging Face, LangChain or LlamaIndex, Pandas, SQL/NoSQL, Parquet/Arrow, Kafka or queues, vector databases, GitHub Actions or Azure DevOps, and MLFlow or W&B.
• Good networking knowledge, scalability testing ability, security-first practices, and cross-domain collaboration skills.

Culture & Benefits

• Hybrid work with flexibility to manage work and personal needs.
• Health and wellbeing benefits for team members and their loved ones.
• Personal and professional development programs supporting career growth and movement across divisions.
• Inclusive work environment that values varied backgrounds and individual uniqueness.