Senior Software Engineer

Who you are

• 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)
• 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

What the job involves

• 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
• 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