Senior AI and HPC Observability Engineer

Description

The company pioneered accelerated computing, including the GPU, and works across gaming, computer graphics, high-performance computing and AI. Its technology supports generative AI and autonomous systems.

The Managed AI Superclusters team builds the infrastructure, platforms and tools that let researchers and engineers develop AI and ML systems.

The role is to build and scale observability and telemetry platforms. The work centres on reliable, high-throughput telemetry pipelines and modern data infrastructure, and the team needs someone with strong distributed systems fundamentals, production-grade coding skills and a focus on keeping systems running well.

Responsibilities

• Build high-performance backend services that ingest, process and route telemetry.
• Design and scale platforms that handle large volumes of metrics, logs and traces across distributed environments.
• Build and optimise metrics pipelines on large-scale time-series storage.
• Develop and extend OpenTelemetry collectors, processors, exporters and instrumentation libraries.
• Design and run real-time and batch telemetry pipelines using streaming and distributed data technologies.
• Improve reliability, performance and cost efficiency through tuning, capacity planning and system optimisation.
• Develop monitoring, alerting and service reliability frameworks that keep the platform healthy.
• Work with platform engineering, infrastructure and site reliability teams to deliver production-grade observability solutions.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering or a related field, or equivalent experience.
• 5+ years of building backend or distributed systems in production.
• Strong programming skills in Python, Go or Java, with experience writing production-quality software.
• Hands-on experience with observability architectures covering metrics, logs and traces.
• Solid experience with PromQL and time-series data systems.
• Experience building or operating distributed data pipelines with technologies such as Kafka, Spark or Flink.
• Experience with Kubernetes and cloud-native infrastructure.
• Strong grasp of distributed systems, concurrency and fault-tolerant design, plus strong debugging, performance tuning and production operations skills.
• Ways to stand out: proven experience designing and scaling observability platforms for AI, GPU or HPC environments.
• Ways to stand out: hands-on expertise with OpenTelemetry, Prometheus, Kafka and high-volume distributed telemetry pipelines.
• Ways to stand out: strong background in data engineering, time-series data modelling and real-time performance tuning.
• Ways to stand out: experience integrating observability with AI/ML pipelines, GPU workload monitoring or intelligent alerting.
• Ways to stand out: demonstrated use of statistical or machine learning techniques for anomaly detection, correlation or predictive insights.

Conditions

Base salary depends on location, experience and other objective job-related factors. The expected range is 152,000 USD to 241,500 USD for Level 3, and 184,000 USD to 287,500 USD for Level 4.

Applications are accepted at least until November 3, 2026.

This posting is for an existing vacancy.

The company uses AI tools in its recruiting processes.

The company is an equal opportunity employer and does not discriminate on any characteristic protected by law.