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Citizen Health

Staff Engineer, Backend

Citizen Health, San Francisco, California, United States, 94199


About UsAt Citizen Health, we're on a mission to revolutionize rare disease research and patient care through the power of data and technology. Founded by individuals with personal connections to rare diseases, we've built a groundbreaking platform that empowers patients to take control of their health information and accelerate scientific breakthroughs. Our team of passionate builders, advocates, clinicians, and engineers is united around an audacious vision: to provide any patient, at any stage of any condition, with immediate access to exceptional personalized guidance.

The RoleWe're seeking a

Staff Backend Engineer

to lead the development of our robust, scalable backend systems that power our patient-centric platform. This role is crucial in designing and implementing the core infrastructure that enables seamless data integration, analysis, and AI-driven insights across our ecosystem.

As a key technical leader, you'll be at the forefront of leveraging healthcare interoperability standards, including FHIR (Fast Healthcare Interoperability Resources), and state-of-the-art AI technologies to build innovative solutions that directly impact rare disease research and patient care.

Your work will be instrumental in translating complex health data into actionable insights, facilitating groundbreaking research, and enabling the seamless flow of information between patients, healthcare providers, and researchers using advanced AI techniques.

ResponsibilitiesArchitect and implement high-performance, scalable backend solutions using modern technologies, healthcare interoperability standards like FHIR, and advanced AI/ML technologiesLead the design and development of RESTful APIs and microservices that support our patient, partner, and internal-facing applicationsIntegrate and optimize AI models, particularly Large Language Models (LLMs), using frameworks like LangChain and LlamaIndexImplement Retrieval-Augmented Generation (RAG) systems to enhance the accuracy and relevance of AI-generated insights in the healthcare contextDesign and implement efficient data pipelines to support AI model training and inferenceOptimize data processing and storage solutions to handle large volumes of complex health data efficientlyCollaborate with data scientists and researchers to implement advanced analytics and AI models that derive insights from patient dataEnsure the highest standards of data security and privacy complianceLead efforts to enhance system reliability and performance, including implementing monitoring, logging, alerting and auto scaling systems for both traditional backend services and AI componentsMentor junior backend developers and contribute to the team's technical growthParticipate in code reviews to ensure high code quality, maintainability, and adherence to best practices across the team

Qualifications7+ years of experience in backend development, with a focus on building scalable, distributed systemsStrong proficiency in one or more modern programming languages (e.g., Python, Java, Go, Scala)Experience with healthcare interoperability standards, particularly FHIRStrong understanding of RESTful API design and microservices architecturesHands-on experience integrating and optimizing Large Language Models (LLMs) in production environmentsProficiency with LLM tools and techniques such as LangChain, LlamaIndex, Prompt EngineeringExperience implementing Retrieval-Augmented Generation (RAG) systemsFamiliarity with vector databases and efficient similarity search techniques for AI applicationsExperience with cloud platforms (preferably AWS) and containerization technologies (e.g., Docker, Kubernetes)Proficiency in working with both relational and NoSQL databasesExperience with message queuing systems and data streaming platformsFamiliarity with data processing and analytics technologies

At Citizen Health, we are committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer and welcome candidates from all backgrounds to apply. We particularly encourage applications from individuals with personal or family experiences with rare diseases, as your insights could be invaluable to our mission.

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