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MEDvidi, Inc. ищет старшего backend инженера (Node.js) для разработки и интеграции AI-автоматизации в телемедицину США.
Вы будете проектировать архитектуру сервисов, внедрять multi-agent workflow, управлять RAG-пайплайнами и обеспечивать масштабируемость, надёжность и observability.
Требуется 8+ лет бэкенд-разработки, опыт с PostgreSQL и AWS, знание LLM-интеграций и английский уровень B2+.
MEDvidi is an AI-powered mental healthcare clinic setting a new standard for safe, effective, and scalable psychiatric care in the United States. We combine licensed providers with proprietary AI tools to deliver consistent, outcomes-driven treatment for conditions like ADHD, anxiety, depression, and more. MEDvidi's technology automates charting, follow-ups, and treatment planning, freeing providers to focus on patient care while improving efficiency and clinical quality. We're looking for a Senior Backend (NodeJS) Engineer to join our AI Automation team and lead the development of AI-driven integrations within our telemedicine platform.
8+ years of commercial backend development with Node.js in product companies (preferably SaaS), with deep understanding of complex backend systems end-to-end. Strong experience designing backend architectures and technical solutions, including system decomposition, scalability trade-offs, long-term maintainability, and technology choices. Proven track record building scalable, high-performance backend systems and robust APIs, with solid understanding of data flows, failure modes, and performance bottlenecks. Hands‑on experience integrating LLMs into production systems (not demos), with focus on reliability, predictability, cost control, and measurable quality improvements. Experience designing and implementing multi-agent AI workflows in production, including orchestration logic, ReAct patterns, supervisor-agent architectures, and clear understanding of when such approaches are justified. Practical experience with modern AI frameworks Solid experience designing and optimizing RAG pipelines: embeddings, vector databases, retrieval strategies, ranking, chunking, and quality vs. latency trade-offs. Strong prompt engineering skills, including structured outputs (JSON/YAML), schema validation, evaluation-based iteration (e.g., AI eval frameworks), and reliability techniques beyond prompt-only solutions. Understanding of LLM infrastructure in production environments: tracing and observability (LangSmith, Langfuse, or similar), evaluation frameworks and quality metrics, tooling and orchestration, safety mechanisms and guardrails, performance and cost optimization. Hands‑on experience with PostgreSQL (schema design, migrations, performance optimization) and AWS (CDK, Lambda, API Gateway, ElastiCache). Good understanding of observability and debugging (Grafana, OpenSearch, or similar). Strong engineering culture: testing, CI/CD, reliability, and technical ownership. Product-oriented mindset with the ability to build user-centered automation, not isolated technical components. Proactive AI enthusiast mindset: explores and validates new AI approaches and patterns applicable to product use cases. Fluent Russian; English B2+. Будет плюсом: Experience working with medical/healthcare AI or regulated environments; Experience with MCP (Model Context Protocol) in Node.js