Senior Software Engineer, Research

About the role

Hippocratic AI is building the first safe, healthcare-focused LLM designed to transform patient outcomes at scale. Our AI agents are already working with real hospitals and health systems.
We need a Senior Research Engineer who can architect systems that don't just work at today's scale, but anticipate tomorrow's growth. You'll own the infrastructure that powers our AI agents, ensuring they're fast, reliable, and ready for the demands of production healthcare.

• Scalable AI Infrastructure: Build backend systems that reliably handle high-volume healthcare data and LLM processing; systems achieve 99.9%+ uptime while supporting exponential growth

• Efficient Data Pipelines: Design and implement data pipelines that ingest, process, and prepare large-scale healthcare datasets for AI training and inference with minimal latency

• High-Performance APIs & Integrations: Develop APIs and microservices that enable seamless data retrieval and AI model interaction; reduce processing time and improve system responsiveness

• Production Reliability & Optimization: Monitor and optimize backend systems for performance and reliability; implement monitoring that catches issues before they impact AI agents in production

• End-to-End ML Enablement: Build infrastructure that enables reproducible ML workflows from data preparation through model deployment; accelerate time-to-production for new AI capabilities

Responsibilities

• Develop and maintain scalable backend systems to support high-performance AI applications in healthcare.

• Collaborate with cross-functional teams, including data scientists and ML engineers, to design and build efficient data pipelines for large-scale healthcare datasets.

• Build and manage APIs and microservices that enable smooth data retrieval, processing, and interaction with AI models.

• Monitor and improve backend systems to optimize performance, reliability, and uptime.

• Work closely with product managers to understand healthcare requirements and help transform them into technical solutions.

• Develop and optimize backend infrastructure supporting data ingestion, feature extraction, and tagging workflows.

• Implement tag management and metadata systems to streamline dataset organization and retrieval.

In-person collaboration: 5 days weekly in Menlo Park—working alongside physicians, ML engineers, and product teams to move healthcare AI forward

Qualification

• Must-Have:
  Bachelor’s degree in Computer Science, Computer Engineering, or a related field. (Master's is preferred)

• 4+ years of experience in backend development using programming languages like Python, Golang, or similar.

• Experience building and maintaining multi-modal data pipelines (speech, vision, and text) using Ray or Apache Airflow for distributed processing and model experimentation.

• Distributed computing with Spark, Hadoop, or similar.
  Familiarity with relational database systems and RESTful APIs.
  Basic understanding of cloud infrastructure (e.g. AWS, GCP).

Preferred:

• Exposure to AI/ML concepts or experience working with LLMs.

• Experience working in teams that handle sensitive or regulated data.

• Familiarity with gRPC, graphQL or similar .

• Experience with real-time audio.

• Exposure to DevOps concepts - CI/CD, deployment, terraform, build systems.

Experience with data science.

Why Join Our Team

• Innovative mission: We are creating a safe, healthcare-focused LLM that can transform health outcomes on a global scale.

• Visionary leadership: Hippocratic AI was co-founded by CEO Munjal Shah alongside physicians, hospital administrators, healthcare professionals, and AI researchers from top institutions, including El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.

• Strategic investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• Team and expertise: We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology.

Why Join Hippocratic AI

Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation.

Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.

Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others.

Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative.

Equal Opportunity

Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact [email protected].

Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.