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Head of Engineering

LlamaIndex - San Francisco, CA, United States - In-office - posted 2026-10-08

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LlamaIndex is seeking a Head of Engineering to lead and develop the engineering organization as the company builds software that makes enterprise data useful for AI applications. You will own engineering execution, technical direction, hiring, and team development. This is a hands-on role where you will work closely with company leadership and product teams to decide what to build, how to build it, and how to deliver it reliably to customers. You should be comfortable reviewing code and architecture, debugging production issues, and writing code for critical systems. Key responsibilities include: - Lead and develop the engineering team, setting clear priorities, ownership, and accountability - Partner with company leadership to translate customer needs into a focused roadmap and deliver software predictably - Stay directly involved in architecture, code reviews, production debugging, and implementation of critical changes - Set technical direction across application services, APIs, data pipelines, and ML infrastructure, balancing immediate customer needs with long-term maintainability - Work with ML engineers and researchers on model training, fine-tuning, evaluation, and deployment - Guide model serving decisions across latency, throughput, GPU utilization, capacity, reliability, and inference cost - Improve engineering practices for testing, observability, security, incident response, and releases - Hire strong engineers, coach technical leaders and managers, and build a culture of direct communication and accountability Required Qualifications: - Experience leading engineering teams in B2B SaaS with responsibility for delivering and operating customer-facing products - Experience leading multiple engineering teams or technical domains with complexity comparable to a 20–30-person organization - Strong, current hands-on engineering skills: ability to read and write production code, review architecture, and diagnose complex technical problems - Practical familiarity with model serving and model training, including training or fine-tuning workflows, evaluation, deployment, and production operations - Understanding of tradeoffs between model quality, latency, throughput, GPU resources, reliability, and cost - Strong background in backend systems, APIs, distributed systems, and cloud infrastructure - Track record of hiring and developing engineers, setting clear expectations, and giving constructive feedback - Good product judgment, including knowing when to move quickly and when to invest in correctness, reliability, and security - Clear written and verbal communication with technical teams, customers, and company leadership Preferred Qualifications: - Experience scaling engineering at a Series A–C startup - Experience with document processing, OCR, extraction, retrieval, indexing, or other systems that work with enterprise data - Experience with LLMs or multimodal models, evaluation datasets, and model quality monitoring - Experience with GPU infrastructure, distributed training, inference optimization, or model serving frameworks - Experience building developer tools or API-first products - Experience with enterprise requirements such as multi-tenancy, access controls, auditability, and security reviews - Experience developing engineering managers while staying closely involved in technical execution

About LlamaIndex

AI / Data / Infrastructure — data framework and cloud tools for connecting enterprise data to LLM applications.

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