Principal AI Engineer - Personalization and Recommendation (Remote)

At Rula, this role owns the applied AI and ML solutions that determine what, how, and how well AI shows up across mental healthcare. The focus isn’t on isolated prototypes, but on building production-grade AI systems that directly power patient-provider matching, clinical workflows, and patient engagement. While your immediate focus will be driving search ranking, relevance, and patient-provider matching, your broader scope encompasses our overarching personalization and recommendation strategies, alongside directing the foundational ML platforms that support them at scale. You’ll operate where applied research, system architecture, and real-world clinical constraints meet. The work spans developing advanced recommendation engines and retrieval models, applying NLP and generative AI to clinical workflows, setting technical standards for AI safety, and making principal decisions about how machine learning is introduced into a high-stakes environment. This is a deeply hands-on role with real technical ownership. You’ll develop and fine-tune models (e.g., Learning-to-Rank, embeddings, recommendation algorithms, and LLMs), design both product-facing AI architectures and core ML infrastructure, unblock complex engineering problems, and act as a technical multiplier for engineers working across product surfaces. Success here means shipping applied AI features that tangibly improve match quality and the user experience, while simultaneously building scalable, durable AI foundations that others can build on confidently.

Responsibilities

Own applied AI and ML solutions for mental healthcare; Drive search ranking, relevance, and patient-provider matching; Oversee personalization and recommendation strategies; Direct foundational ML platforms that support them at scale; Develop and fine-tune models such as Learning-to-Rank, embeddings, recommendation algorithms, and LLMs; Design product-facing AI architectures and core ML infrastructure; Set technical standards for AI safety; Act as a technical multiplier for engineers; Make principal decisions about how machine learning is introduced into a high-stakes environment

Requirements

10+ years of software engineering, including 7+ years of experience designing and scaling distributed systems, and 5+ years building and deploying production-grade ML applications.; 5+ years of deep, hands-on experience building and optimizing search, ranking, relevance, or recommendation engines at scale (e.g., Learning-to-Rank, collaborative filtering, deep recommender systems, semantic vector search); 5+ years of strong programming experience in Python and at least one backend language (preferably TypeScript, Java, or Go), combined with 2+ years of experience building AI-powered products using foundation models (OpenAI, Anthropic, Gemini) and LLM integration patterns (RAG, agents, etc.); Strong proven track record working with both traditional search/retrieval infrastructure (e.g., Elasticsearch, OpenSearch) and modern vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus); 3+ years of experience with MLOps, data pipelines, and rigorous evaluation systems (offline metrics like NDCG/MAP, online A/B testing), with a demonstrated ability to define technical strategy and guide the broader AI/ML infrastructure ecosystem

Nice to have

Experience architecting secure and compliant AI solutions in regulated environments (HIPAA, GDPR, etc.); Familiarity with human-in-the-loop systems and clinical decision support frameworks.; Experience designing evaluation pipelines for human alignment, factual accuracy, or model interpretability.; Contributions to open-source AI frameworks or applied research in NLP, healthcare AI, or GenAI safety.; Experience contributing to early-stage team growth (0 → 1); Experience leading or mentoring engineering teams in AI, ML platform, or applied research domains

Benefits

100% remote work environment; Working hours to support a healthy work-life balance; Attractive pay and benefits; Full transparency of pay ranges regardless of where you live in the United States; Comprehensive health benefits: Medical, dental, vision, life, disability, and FSA/HSA; 401(k) plan access; Generous time-off policies including 2 company-wide shutdown weeks each year for self-care; Paid parental leave for all parents, including birthing, non-birthing, adopting, and fostering; Employee Assistance Program (EAP); Quarterly department stipend; Community and employee resource groups; Home office stipend: New hire home office stipend & $50 monthly stipend to help cover internet or cell phone expenses; Wellness at Rula program: Year-round wellness initiatives and a $50/month wellness stipend