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Director, AI Platform Reliability

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: logicmonitor
Full Time position
Listed on 2026-09-09
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below

About Us:

We love going to work and think you should too. Our team is dedicated to trust, customer obsession, agility, and striving to be better everyday. These values serve as the foundation of our culture, guiding our actions and driving us towards excellence. We foster a culture of performance and recognition, allowing us to transform growth as we enable our employees to do the best work of their careers.

This role is open to candidates based in or near San Francisco, CA. At Logic Monitor, we hire within our Centers of Energy-vibrant locations where our teams connect, collaborate, and innovate.

To learn more about life at Logic Monitor, check out our Careers Page .

What You'll Do:

Logic Monitor® is the AI-first hybrid observability platform powering the next generation of digital infrastructure. Logic Monitor delivers complete visibility and actionable intelligence across on-premises, cloud, and edge environments. By anticipating issues before they strike, optimizing resources in real time, and enabling faster, smarter decisions, Logic Monitor helps IT and business leaders protect margins, accelerate innovation, and deliver exceptional digital experiences without compromise.

Our customers love Logic Monitor’s ability to bring cloud and traditional IT together into one view, as seen in minimal churn rates, expansion business, and exciting new customer references. In fact, Logic Monitor has received the highest Net Promoter Score of any IT Infrastructure Management provider. Logic Monitor also boasts high employee satisfaction. We have been certified as a Great Place To Work®, and named one of Built In’s Best Places to Work for the seventh year in a row!

We are looking for an accomplished and hands‑on Director of AI Platform Reliability to lead the architecture, development, and operation of highly scalable, distributed software platforms.

This leader will be responsible for systems that process hundreds of millions/billions of transactions and events , manage terabytes to petabytes of data , and deliver reliable, low‑latency services to enterprise customers. The ideal candidate combines strong engineering depth in Java, Kafka, distributed systems, and cloud‑native microservices with a demonstrated ability to build and lead high‑performing engineering organizations.

This is a strategic leadership role, but it requires a leader who can remain close to the technology, participate in architecture reviews, challenge design decisions, guide teams through complex production problems, and establish the engineering practices required to operate mission‑critical platforms at scale.

Here’s a closer look at this key role:

  • Lead and scale multiple engineering teams responsible for high-volume, business‑critical distributed systems and data platforms.
  • Define the technical strategy and architecture for platforms processing hundreds of millions of transactions and terabytes of data.
  • Guide the development of Java‑based microservices, APIs, Kafka streaming pipelines, batch‑processing workflows, and cloud‑native services.
  • Build and evolve scalable data lake and Data Lakehouse platforms supporting real‑time, near‑real‑time, and batch analytics workloads.
  • Establish reliable data ingestion, transformation, storage, governance, lineage, retention, and data‑quality practices across streaming and batch pipelines.
  • Build low‑latency, highly available, fault‑tolerant systems with strong scalability, resiliency, and disaster‑recovery capabilities.
  • Define and own operational SLAs, SLOs, availability targets, recovery objectives, and performance metrics for critical services and data pipelines.
  • Drive capacity planning, load testing, throughput optimization, and improvements to p95 and p99 latency.
  • Ensure effective Kafka design, including partitioning, consumer groups, ordering, schema evolution, replay, and lag management.
  • Establish engineering standards for architecture, coding, testing, security, observability, and production readiness.
  • Partner with Product, Architecture, SRE, Security, Data, and Infrastructure teams to deliver strategic platform initiatives.
  • Strengthen operational excellence through monitoring, incident management,…
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