Senior Ai Software Developer (Xico) (Valle de Chalco Solidaridad)

RELOCATION TO PUERTO RICO IS REQUIRED

This role is based at a site in San Juan, Puerto Rico, offering the opportunity to work closely with a dynamic team in a highly collaborative environment. The company supports top talent and provides a comprehensive relocation package to make your transition seamless and exciting.

Senior AI Software Developer – Overview

We are seeking a highly skilled and experienced Senior AI Software Developer to join our innovative team. This hybrid role requires working from an office for an average of two days per week.

Our company is committed to advancing the way people live and work by helping organizations connect, protect, analyze, and act on their data and applications. If you are passionate about artificial intelligence, cutting‑edge technology, and making a meaningful impact, we invite you to explore this exciting opportunity.

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 while maintaining high code quality and documentation.
• Modeling & Evaluation : Fine‑tune models as needed and design evaluation harnesses and metrics. Build A/B testing setups and track accuracy, latency, robustness, and task success rates. Conduct error analysis and iterate using feedback efficacy loops and prompt refinement.
• Data & Retrieval Engineering : Build ETL/ELT pipelines and curate datasets with metadata, lineage, and validation. Implement vector indexing, tune chunk size and overlap, and enforce data governance.
• MLOps & Platform Readiness : Containerize workloads using Docker and orchestrate deployments with Kubernetes/Helm. Manage CI/CD pipelines for machine learning workflows, including training, evaluation, packaging, deployment, monitoring, and rollback. Maintain model/agent registries, experiment tracking, and reproducible environments.
• Software Engineering & Integration : Build microservices and asynchronous inference paths, supporting batch and stream processing. Integrate with enterprise authentication, observability, telemetry, and logging systems. Write unit, integration, end‑to‑end tests, performance benchmarks, and failure‑injection tests.
• Observability, Reliability & Performance : Instrument systems with metrics, logs, and traces, and define SLOs for latency, throughput, and error rates. Optimize inference through batching, caching, quantization, and token efficiency. Implement guardrails, safety filters, jailbreak detection, auto‑evaluations, and alerts.
• Security & Compliance : Apply secure coding practices and manage secrets, encryption, and least privilege access. Ensure compliance with data residency, consent, and audit trail requirements. Enforce policy‑based access and content safety in user‑facing features.
• Collaboration & Mentoring : Review designs and pull requests, and coach junior engineers on best practices. Collaborate with AI Architects, Data Engineers, QA teams, and Product Managers.

Qualifications

• Education & Experience : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, Artificial Intelligence, or a related quantitative discipline. 7–10 years of relevant experience in software development and AI/ML engineering.
• Required Skills : Expertise in LLMs, prompt engineering, function/tool calling, and orchestration frameworks. Proficiency in Python (FastAPI/Flask), microservices patterns, and backend development. Strong knowledge of MLOps tools (Docker, Kubernetes, CI/CD pipelines, GPU scheduling). Experience with frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain. Familiarity with vector databases (FAISS, Milvus, Pinecone, etc.) and data engineering tools (Pandas, SQL/NoSQL, Kafka). Strong understanding of observability, metrics, logging, and automated evaluation pipelines.
• Additional Skills : Cross‑domain knowledge, scalability testing, security‑first mindset, and design thinking.

Day‑to‑Day

• Collaborate with cross‑functional teams to design and implement AI‑driven solutions.
• Develop and deploy robust, scalable, and secure AI systems.
• Monitor system performance, troubleshoot issues, and optimize for efficiency.
• Mentor junior engineers and contribute to a culture of continuous learning and innovation.
• Stay updated on the latest advancements in AI and machine learning technologies.

Benefits

• Health and wellbeing support, including comprehensive suite of benefits for physical, financial, and emotional wellbeing.
• Personal and professional development programs to help you achieve professional goals.
• Unconditional inclusion and inclusive environment fostering diverse backgrounds.
• Flexibility to balance work and personal needs while contributing to a positive work culture.