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Starburst is hiring a Head of Engineering to lead the AI Platform (SAIL) team in India. This is a foundational leadership role—not a satellite team, but an autonomous charter with full ownership of hiring, roadmap, and customer outcomes.
The role centers on building an agent platform across three interconnected arcs: (1) an internal agent platform serving Starburst's own engineers, with SDKs, evaluation frameworks, guardrails, and model serving infrastructure; (2) hardening that platform for external customers with multi-tenancy, security, and stable APIs; and (3) observability systems that let both internal teams and enterprise customers understand agent behavior, cost, and performance.
You will be a player-coach, writing code alongside your first hires and gradually shifting toward leadership as the team scales. Key responsibilities include owning the agent platform roadmap, hiring and developing senior engineers in India, making architecture decisions for the SDK and serving infrastructure, running the platform with production discipline (on-call, incident response, root-cause analysis), operating autonomously across time zones, and engaging directly with enterprise customers when platform capabilities are at stake.
The ideal candidate has 10+ years of engineering experience with 3+ years leading teams through full cycles (hiring, shipping, growing people). You should have built platform or infrastructure products for multiple engineering teams and can discuss interface contracts, adoption curves, and intentional trade-offs. Production LLM systems experience is essential—you understand the difference between demos and enterprise-grade systems, including LLMOps, timeout/retry design, token cost discipline, latency budgets, and failure modes. You are product-curious, asking who the user is before designing architecture, and you have sat with users and changed course based on feedback.
Nice-to-haves include experience taking internal platforms external, agentic systems and evaluation methodology, comfort across Python and JVM ecosystems, data systems or analytics product experience, and multi-model platform experience in regulated environments.
