Job Description

💻 Staff / Principal Software Engineer – AI Platform (LLMs & RAG)

📋 GenAI Healthcare

📍 Hybrid in SF

💸 Competitive base + hefty bonus

We are working with a pioneering generative AI-native health company revolutionizing hyper-personalized care. Its precision care platform enabling a new era of whole-person care through generative and predictive intelligence. They tap into cutting-edge resources, have an extensive dataset covering 100s million patients and a network of 1.8 million healthcare professionals.

We are seeking a Staff / Principal Software Engineer to provide technical leadership in building, scaling, and operating LLM-powered healthcare applications, with a strong emphasis on RAG, knowledge systems, and AI-native backend architectures.

Responsibilities:

• Design, build, and evolve scalable LLM-based systems, including RAG pipelines, prompt orchestration, embedding strategies, vector search, and inference workflows.
• Develop AI services that operate on healthcare and clinical data while respecting FHIR, HL7, HIPAA, and other regulatory and compliance requirements.
• Partner closely with clinical, product, and data science teams to translate real-world clinical workflows
• Build and maintain backend services and APIs supporting LLM inference, evaluation, observability, and lifecycle management
• Establish best practices for prompt management, model versioning, human-in-the-loop workflows, and continuous improvement using feedback signals.
• Act as a technical authority across teams, influencing architecture decisions and long-term platform strategy.
• Mentor senior and mid-level engineers, set engineering standards, and raise the bar on system design and code quality.
• Work closely with data engineering, data science, security, and product leadership to align AI capabilities with business and clinical objectives.

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 7+ years of professional software engineering experience, with 2+ years working directly with LLM-based systems in production environments.
• Hands-on experience designing and deploying RAG architectures
• Strong proficiency in Python and experience with modern backend stacks
• Experience working in healthtech, healthcare, life sciences, or clinical data environments, including exposure to regulated data.
• Proven ability to design systems that are scalable, secure, observable, and maintainable.

Preferred Qualifications:

• Experience integrating LLMs with EHR data, clinical guidelines, prior authorization rules, quality measures, or real-world evidence datasets.
• Familiarity with LLM evaluation tooling and frameworks
• Experience with cloud-native architectures and containerized deployments

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