Job Description
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Company Overview
A leading AI infrastructure and software organization provides an end-to-end platform for developing, deploying, and scaling artificial intelligence applications. The organization combines high-performance cloud infrastructure with tools for experiment tracking, model optimization, AI agent development, observability, training, and inference.
Key Responsibilities
- Lead an engineering team focused on delivering an enterprise-grade AI observability platform.
- Optimize the platform for large-scale data ingestion and processing across major cloud platforms.
- Partner with sales teams to support new customer opportunities and existing enterprise customers.
- Monitor and optimize single-tenant deployments and support customer-managed deployments.
- Establish and enforce service-level agreements (SLAs) and service-level objectives (SLOs) for availability and data readiness.
- Lead optimization of infrastructure and data storage components to improve performance and cost efficiency.
- Own engineering roadmaps, execution, hiring, team development, and organizational priorities.
- Hire, coach, mentor, and develop engineers while fostering a culture of technical excellence.
- Report on system health and participate in broader product and engineering roadmap planning.
- Own end-to-end delivery of production services, including planning, execution, quality, reliability, and operational health.
- Participate in on-call rotations and incident response activities.
- Work closely with cross-functional stakeholders to balance customer requirements, technical priorities, and business objectives.
Required Qualifications
- 1–3 years of experience as an engineering manager with people leadership responsibilities.
- 6+ years of professional software engineering experience.
- Experience working with external customers on platform or product implementations.
- Experience leading teams that have delivered enterprise software at scale.
- Experience with single-tenant and on-premises deployments.
- Experience working with large-scale data stores and systems with compliance, security, scalability, and performance requirements.
- Strong understanding of service availability and performance metrics, SLAs, SLOs, and incident response processes.
- Understanding of AI observability concepts, workflows, and requirements.
- Ability to collaborate effectively with sales organizations and participate in customer calls.
- Experience owning end-to-end delivery of production services.
- Strong sense of ownership with the ability to drive measurable impact and results.
- Excellent written and verbal communication skills.
- Ability to align engineering, product, finance, compliance, and other stakeholders around priorities and tradeoffs.
- Bachelor’s degree in Computer Science or a related field.
- Located in the San Francisco Bay Area and available to work from the San Francisco office at least a few days per week.
Preferred Experience
- Experience evaluating single-tenant architecture tradeoffs within SaaS environments.
- Familiarity with modern data technologies such as ClickHouse, Kafka, and Kubernetes for high-throughput data processing.
- Previous experience in MLOps or AI observability, particularly supporting LLM application development workflows.
- Experience working in a fast-paced startup environment during periods of rapid growth.
- Experience supporting enterprise adoption of emerging software technologies.
- Strong interest in coaching engineers on system design, correctness, and large-scale enterprise engineering requirements.
- Ability to operate effectively in ambiguous environments while balancing short-term delivery with long-term architectural investments.
- Strong understanding of enterprise software requirements and technical tradeoffs.
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