Senior Backend Engineer | $7.5B AI Healthtech Startup

Job Description About Day One Partners /n Day One Partners is a search firm that partners with venture capital firms to help build high-growth startups. We lead confidential searches for leadership and critical roles across a range of company stages, industries, and functions /n /n About The Role /n We’re partnering with a healthcare technology company expanding the engineering team behind a sophisticated AI platform. This role is focused on the reliability and scale of production services that handle large amounts of unstructured data and support machine learning applications. /n /n What You’ll Do: /n /n - Design and improve distributed services that support high volume, compute intensive workloads. /n - Develop data pipelines that handle both live and asynchronous processing. /n - Work with audio and media systems, including ingestion, transformation, storage, and lifecycle management. /n - Connect production services with transcription, language models, and other machine learning components. /n - Design recovery patterns for interrupted requests, duplicate events, timeouts, and unavailable dependencies. /n - Improve latency, throughput, reliability, and infrastructure efficiency as usage grows. /n - Give engineering teams better visibility into production behavior through logging, metrics, tracing, and diagnostic tools. /n - Design APIs and data models for processes that span multiple services. /n - Work closely with product, AI, application, security, and healthcare domain teams. /n /n /n What You’ll Bring: /n /n - 4+ years of backend or infrastructure engineering experience. /n - Experience designing and operating distributed systems at production scale. /n - Strong knowledge of asynchronous processing, queues, concurrency, idempotency, and data consistency. /n - Experience deploying, monitoring, and scaling services in the cloud. /n - Strong proficiency in at least one modern backend programming language. /n - Experience with technologies such as Temporal, Kafka, Kubernetes, or similar platforms is a plus. /n - Exposure to media systems or production machine learning infrastructure is also valuable. /n /n /n Why You’ll Love This Role: /n /n - Tackle meaningful engineering problems across distributed computing and AI. /n - Take substantial ownership of architecture and production reliability. /n - Work closely with both product and machine learning teams. /n - Help shape technical practices as the engineering organization grows. /n