We are seeking a highly skilled Senior AI Software Developer to join our innovative team in San Juan, Puerto Rico. The role involves translating high-level designs into component contracts, implementing LLM integrations and RAG pipelines, fine-tuning models, building ETL pipelines, containerizing workloads with Docker/Kubernetes, and mentoring junior engineers. Candidates must have 7-10 years of software development and AI/ML experience with expertise in Python, MLOps tools, and LLM technologies.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
*RELOCATION TO PUERTO RICO IS REQUIRED*
This role is based on site in vibrant city of San Juan, Puerto Rico, offering the opportunity to work closely with a dynamic team in a highly collaborative environment. The company is committed to supporting top talent and proudly 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
As a Senior AI Software Developer, you will:
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.
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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.
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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
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- 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 & Wellbeing
We offer a comprehensive suite of benefits to support your physical, financial, and emotional wellbeing, ensuring you and your loved ones are cared for.
Personal & Professional Development
We invest in your career growth through tailored programs designed to help you achieve your professional goals, whether you aim to deepen your expertise or explore new opportunities within the organization.
Unconditional Inclusion
We celebrate individual uniqueness and foster an inclusive environment where diverse backgrounds are valued and thrive. We provide the flexibility to balance work and personal needs while making bold moves together as a force for good.
Join us and be part of a team that is shaping the future of technology. Apply today to make a meaningful impact and accelerate what’s next!
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