AI Engineer (LLM / Python) at MedTrainer

<div class="content-intro"><h2 data-start="116" data-end="443"><span class="hover:entity-accent entity-underline inline cursor-pointer align-baseline"><span class="whitespace-normal">Company Description</span></span></h2> <p data-start="116" data-end="443"><span class="hover:entity-accent entity-underline inline cursor-pointer align-baseline"><span class="whitespace-normal">MedTrainer</span></span> is the only all-in-one compliance platform purpose-built for healthcare organizations, by healthcare professionals. For over 13 years, we have helped healthcare teams remain audit-ready and confident in their regulatory compliance through continuous innovation and deep industry expertise.</p> <p data-start="445" data-end="835">Our cloud-based platform unifies learning management, credentialing, and compliance into a single intelligent system designed to simplify complex healthcare operations. Powered by automation and AI-driven workflows, MedTrainer enables organizations to onboard faster, streamline processes, and scale efficiently while maintaining the highest standards of compliance and workforce readiness.</p> <p>&nbsp;</p></div><p>We are looking for people who are curious, collaborative, and excited to build reliable technology that supports a mission-driven healthcare platform. Be part of a great engineering team that constantly challenges its status quo to build the best product in the industry alongside our Product and DevOps teams.</p> <h2>Job Description</h2> <p><br>Looking for a <strong>Senior Software Engineer - AI</strong> to design, build, and operate LLM-powered product features and internal AI tooling that drive real business value for healthcare organizations. You will take AI capabilities from prototype to production, working with LLM APIs, retrieval-augmented generation (RAG), embeddings and vector databases, and agentic workflows, while making sure every solution is measurable, reliable, cost-efficient, secure, and HIPAA-aware. This role collaborates closely with Product, DevOps, and Data/IT teams, breaks down ambiguous problems into actionable tasks with minimal oversight, and helps establish AI engineering best practices, evaluation standards, and responsible AI guidelines across the organization.&nbsp;</p> <h2>Responsibilities</h2> <ul> <li><strong>Build AI Product Features:</strong> Design, develop, and ship LLM-powered features (assistants, intelligent search, summarization, content and document generation) into the MedTrainer platform, from prototype to production.</li> <li><strong>RAG and Retrieval:</strong> Build and tune retrieval-augmented generation pipelines, including document ingestion, chunking, embeddings, vector search, re-ranking, and grounded answers with citations.&nbsp;</li> <li><strong>Agents and Internal AI Tooling:</strong> Create agents, tool/function-calling workflows, and internal AI tools that automate processes and boost productivity across Engineering, Product, and operations.&nbsp;</li> <li><strong>Evaluation and Quality:</strong> Own prompt engineering and evaluation by building eval datasets, automated and LLM-as-judge evals, and regression tests that gate releases and prove quality improvements.&nbsp;</li> <li><strong>Production Engineering:</strong> Develop Python services and APIs that integrate with our existing platform (PHP/Node), deployed with Docker, Kubernetes, and GitHub Actions on Azure/AWS, with observability for quality, latency, and cost.</li> <li><strong>Security, Privacy, and Responsible AI:</strong> Apply HIPAA-aware data handling, PHI/PII minimization and redaction, prompt-injection defenses, guardrails, and human-in-the-loop controls where needed.&nbsp;</li> <li><strong>Collaboration and Culture:</strong> Partner with Product, DevOps, and Data/IT to define success metrics, communicate progress and trade-offs clearly, and share AI knowledge and best practices across the team.&nbsp;</li> </ul> <h2>Qualifications</h2> <ul> <li><strong>Education:</strong> Bachelor’s degree in Computer Science, an equivalent degree, or equivalent professional experience.</li> <li><strong>Professional Experience:</strong> 4+ years of software engineering experience, including at least 1 year building and operating LLM/ML-powered features in production.&nbsp;</li> <li><strong>Methodological Background:</strong> Proven experience working within structured Agile/Scrum development environments.&nbsp;</li> <li><strong>Language Proficiency:</strong> Advanced English skills are considered a plus.</li> </ul> <h2>Essential Technologies and/or Skills</h2> <ul> <li><strong>LLMs and APIs:</strong> Hands-on experience with LLM APIs such as OpenAI, Anthropic, and/or Azure OpenAI, including structured outputs, streaming, and function/tool calling.&nbsp;</li> <li><strong>RAG, Embeddings, and Vector Databases:</strong> Practical experience with embeddings, vector databases (pgvector, Pinecone, Qdrant, Azure AI Search, or similar), and retrieval strategies such as hybrid search and re-ranking.</li> <li><strong>Prompt Engineering, Evals, and Agents:</strong> Strong prompt engineering skills, experience building evals, and familiarity with agent/orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent).&nbsp;</li> <li><strong>Backend and APIs:</strong> Strong Python skills (FastAPI or similar) and REST API design; familiarity with PHP (Symfony) or Node.js is a plus. Experience with Model Context Protocol (MCP) and AI-assisted development tools is a plus.&nbsp;</li> <li><strong>Cloud, Containers, and CI/CD:</strong> Experience with Azure and/or AWS, Docker, Kubernetes, and CI/CD with GitHub Actions, plus observability of AI systems (tracing, logging, token and cost monitoring). Git, Jira, and Software Development Lifecycle best practices.&nbsp;</li> <li><strong>Performance, Security, and Compliance:</strong> Cost and latency optimization of LLM workloads, security and privacy best practices, HIPAA-aware handling of sensitive data, and responsible AI principles. Healthcare or regulated-industry experience is a plus.&nbsp;</li> </ul> <h2>Additional Information</h2> <ul> <li><strong>Work Location:</strong> 100% remote work from anywhere within Mexico.</li> <li><strong>Compensation:</strong> Competitive monthly salary (paid after taxes).</li> <li><strong>Health and Wellness:</strong> Major Medical Insurance and healthcare coverage, along with wellness benefits such as TotalPass gym discounts.</li> <li><strong>Home Office Support:</strong> Financial support for home office setup and ergonomics (including internet, electricity, and an office chair disccount).</li> <li><strong>Growth and Development:</strong> Professional development opportunities, including company-provided English classes.</li> <li><strong>Financial Benefits:</strong> Savings plan.</li> <li><strong>Time Off:</strong> Paid time off, including personal days.</li> <li><strong>Culture and Tech Stack:</strong> A collaborative, international, and growth-oriented environment with an engineering culture focused on automation, reliability, and continuous improvement. You will have the opportunity to work with modern cloud infrastructure, leading LLM platforms, and AI-assisted development tools.</li> </ul> <p>All received information will be kept confidential according to EEO guidelines.</p><div class="content-pay-transparency"><div class="pay-input"><div class="title">Salary range</div><div class="pay-range"><span>$55,000</span><span class="divider">&mdash;</span><span>$70,000 MXN</span></div></div></div><div class="content-conclusion"><p data-start="105" data-end="307"><strong>At MedTrainer, every role contributes to building technology that supports safer, more efficient healthcare organizations. We value collaboration, ownership, and continuous improvement across all teams.</strong></p> <p data-start="309" data-end="419" data-is-last-node="" data-is-only-node=""><strong>If you’re excited to grow, make an impact, and be part of a mission-driven company, we encourage you to apply.</strong></p></div>