Software Engineer, Backend AI Infrastructure

Location: Palo Alto, CA (On-site)

Team: Engineering

About the Company

This company is at the forefront of a technological revolution in healthcare, dedicated to engineering the industry's first safety-first Large Language Model. The mission is to create a seismic shift in global health equity by making profound medical expertise universally accessible. The work here represents a unique convergence of cutting-edge artificial intelligence and human well-being, with the potential for impact on a billion-person scale.

The organization was established by a coalition of visionary leaders—including accomplished physicians, hospital executives, and AI pioneers from elite institutions and technology giants. This foundation ensures that product development is guided by real-world clinical wisdom from day one. The company is backed by over a quarter-billion dollars in funding from the world's most discerning technology and healthcare investors, alongside strategic partnerships with major health systems, providing unparalleled resources and market credibility.

The culture is built on the principle that radical collaboration drives breakthrough innovation. To that end, the team works together in person, five days a week, at the company's headquarters in Palo Alto.

About the Role

We are seeking a skilled Software Engineer to join a tight-knit, multidisciplinary team of engineers, applied researchers, and healthcare domain experts. This role is central to constructing the robust backend infrastructure that powers our generative AI platform. You will be tasked with building systems that are not only high-performing and scalable but also secure and reliable enough to meet the rigorous demands of the healthcare sector.

Your contributions will directly enable the development of AI-driven solutions that process complex, large-scale datasets, requiring a meticulous approach to data integrity, privacy, and system resilience. This is an opportunity to engineer the core plumbing that allows groundbreaking AI to safely and effectively reach patients and providers.

Key Responsibilities

1. Design, build, and maintain scalable backend services and distributed systems that form the foundation for high-stakes AI applications in healthcare.
2. Engineer efficient, secure data pipelines capable of handling large-scale, sensitive healthcare datasets in collaboration with ML and data science teams.
3. Develop and manage robust APIs and microservices to facilitate seamless data interaction, processing, and integration with our AI models.
4. Implement and uphold stringent data security, privacy, and compliance protocols to safeguard protected health information.
5. Continuously monitor, troubleshoot, and optimize system performance, reliability, and availability.
6. Partner with product management to translate complex healthcare requirements into pragmatic and scalable technical solutions.
7. Actively participate in a collaborative engineering culture through code reviews, architectural discussions, and knowledge sharing.

Qualifications & Experience

Foundational Requirements:

1. A Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
2. 5+ years of professional backend development experience, with proficiency in languages such as Python or Golang.
3. Proven expertise in building and maintaining SaaS control planes, relational databases, and RESTful API architectures.
4. Strong hands-on experience with cloud infrastructure (e.g., AWS, GCP) and container orchestration platforms like Kubernetes.
5. Excellent problem-solving abilities and a growth-oriented mindset.

Specialized Experience (We are looking for proficiency in one or more of the following areas):

1. AI Agent Frameworks: Experience in building modern, agentic frameworks and orchestration platforms that empower LLM-based agents to execute complex tasks.
2. Conversational AI Systems: A background in designing and deploying production-level conversational AI systems, utilizing either third-party platforms or bespoke in-house technology.
3. Production LLM Applications: A track record of developing and scaling production-grade LLM applications or autonomous agents that are integrated into real-world user workflows.

Additional Valued Experience:

1. Familiarity with core AI/ML concepts and practical experience working with Large Language Models.
2. Exposure to developing software within regulated environments or for applications that handle sensitive data.
3. Proficiency with technologies such as SQLAlchemy, Flask, and asynchronous programming patterns.

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