Head of Engineering
LlamaIndex provides AI document-processing and knowledge-agent infrastructure, centered on LlamaParse for parsing, extraction, indexing, and retrieval over unstructured enterprise documents.
Maintainer signals as of 9/25/2026
About LlamaIndex
A San Francisco AI company offering a developer-first platform and commercial APIs for document workflows and knowledge agents. Its active products include LlamaParse, agentic OCR and structured extraction software, and the open-source local document parser LiteParse.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead engineering execution, set technical direction, and develop the engineering organization. You will work with leadership and product teams to turn customer needs into a focused roadmap and reliable software delivery. You will remain hands-on through architecture reviews, code reviews, production debugging, and critical implementation work. You will guide application services, APIs, data pipelines, ML infrastructure, model training, evaluation, deployment, and serving decisions. You will strengthen testing, observability, security, incident response, and release practices while hiring and coaching engineers and technical leaders.
Requirements
- Experience leading multiple engineering teams in B2B SaaS at a scope comparable to a 20–30-person organization.
- Current hands-on engineering skills in production code, architecture review, and complex technical problem diagnosis.
- Familiarity with model serving and training, including fine-tuning, evaluation, deployment, and production operations.
- Understanding of tradeoffs among model quality, latency, throughput, GPU resources, reliability, and cost.
- Background in backend systems, APIs, distributed systems, and cloud infrastructure.
- Track record of hiring and developing engineers, setting expectations, and providing feedback.
- Product judgment balancing speed, correctness, reliability, and security.
- Clear written and verbal communication with technical teams, customers, and leadership.
Responsibilities
- Lead and develop the engineering team, setting priorities, ownership, and accountability.
- Translate customer needs into a focused roadmap and deliver software predictably.
- Review architecture and code, debug production issues, and implement critical changes.
- Set technical direction for application services, APIs, data pipelines, and ML infrastructure.
- Work on model training, fine-tuning, evaluation, deployment, and production operations.
- Guide model-serving decisions across latency, throughput, GPU utilization, capacity, reliability, and inference cost.
- Improve testing, observability, security, incident response, and release practices.
- Hire engineers, coach technical leaders and managers, and foster accountability.
Benefits
- Equity
