AI Production Engineer

AI Production Engineer ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business. WHAT WE ARE LOOKING FOR At Distyl, AI systems live or die on latency, reliability, and operational excellence. AI Production Engineers focus on building and operating AI systems that perform in real time, at scale, under strict reliability constraints. They work with the rest of the forward deployed team to ensure our AI systems are reliable, performant, and secure from the ground up. These engineers are hands-on system owners who bring deep expertise in production engineering—low-latency services, voice pipelines, batch processing, and observability—while remaining fully accountable for the behavior and value of customer-facing AI systems. They thrive in high-performance environments and take personal ownership of making sure AI systems are fast, stable, and trustworthy in production. KEY RESPONSIBILITIES - Own the performance and reliability characteristics of AI systems deployed in customer environments - Design, build, and operate low-latency AI services—including real-time voice and interaction pipelines—as well as large-scale batch processing workflows that execute complex AI workloads reliably - AI Production Engineers are the escalation point for performance and reliability risk, and have veto power on launches that violate production constraints - Deeply involved in system design, implementation, and operation, investigating performance bottlenecks, failure modes, and scaling limits across AI pipelines, APIs, orchestration layers, and infrastructure - Design and evolve observability systems—metrics, logs, tracing, alerts—that make AI behavior understandable and actionable in production - Work directly with Forward Deployed AI Engineers, Product Engineers, and Architects to ensure that production constraints meaningfully shape system design - Step in on high-risk or high-impact issues, debug live systems, and harden AI services so they can operate continuously under real-world load - Help turn one-off production solutions into reusable patterns and platform capabilities, raising the overall production bar for Distyl’s AI systems over time WHAT WE REQUIRE - 3+ years of software engineering experience - Deep Production Engineering Experience: Built and operated high-scale systems—low-latency APIs, streaming pipelines, real-time services, or large batch processing systems—and can reason deeply about performance, throughput, and reliability. Experience with real-time voice systems is a strong plus - Strong Systems and Backend Fundamentals: Write high-quality production code and understand distributed systems concepts such as concurrency, fault tolerance, backpressure, and graceful degradation. You are comfortable optimizing systems under tight latency and throughput constraints - Operational Excellence Mindset: Treat observability, instrumentation, and incident ... (truncated, view full listing at source)