Senior Staff AI Engineer, Rula

• 10+ years of software engineering, including 7+ years of experience with Public Cloud (AWS, GCP, etc.), 5+ years designing and scaling distributed systems
• 5+ years of deep experience in Python and at least one backend language (preferably JavaScript, TypeScript, Java, or Go)
• 2+ years of proven track record building AI-powered products at scale, including hands-on experience with foundation models (OpenAI, Anthropic, Bedrock, Gemini, etc.)
• 2+ years of strong experience in LLM integration patterns (RAG, function calling, agents, memory routing, etc.), or AI orchestration frameworks (eg. LangChain, LlamaIndex, DSPy, Haystack), or vector databases (eg. Pinecone, Weaviate, FAISS, Milvus)
• 3+ years in working with MLOps, data pipelines, evaluation, and observability systems for continuous model improvement

Desirable

• At Rula, this role owns the AI foundation that determines how, and how well, AI shows up across mental healthcare
• The focus isn’t on prototypes or isolated features, but on building durable, production-grade generative AI systems that directly power patient engagement, provider workflows, and clinical operations at scale
• You’ll operate where architecture, applied research, and real-world constraints meet
• The work includes designing core AI platforms, setting technical standards for safety, reliability, and performance, and making principald decisions about how advanced AI is introduced into a regulated, high-stakes care environment
• The goal is simple but hard: make AI genuinely useful in clinical contexts, without compromising trust or outcomes
• This is a deeply hands-on role with real technical ownership
• You’ll define system architecture, unblock complex engineering problems, and act as a technical multiplier for other engineers working across product surfaces
• Success here means creating foundations that others can build on confidently and that hold up under scale, scrutiny, and real patient impact
• The opportunity is less about chasing the frontier for its own sake and more about shaping how AI responsibly becomes part of everyday mental healthcare, setting direction not just for what we build next, but for how AI evolves inside the care ecosystem over time