Manager, Software Engineering - Observability

Навыки

• Атрибуция
• Data Quality
• Datadog / New Relic
• Распределённые системы
• Форензика и реагирование
• Jaeger / OpenTelemetry
• Лидерство

О компании и продукте

• Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!. Figma’s Observability engineering team builds and operates the systems that give us deep visibility into the health, performance, and efficiency of our platform. From metrics, logs, and traces to cost attribution and budgeting, this team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability and spend

Задачи

• Lead and grow a team of 5 engineers responsible for the reliability, scalability, and evolution of Figma’s Observability and AI Trace Observability platforms
• Own and operate the AI Trace Observability ecosystem, including a safe telemetry pipeline that aggregates all relevant data, runs it through classification and then gives engineers the ability to run evals against this data
• Own and operate Figma’s core observability stack, including vendor platforms such as Datadog, ensuring high availability, strong data quality, and effective signal-to-noise across metrics, logs, and traces
• Define and drive the technical strategy for instrumentation standards, observability libraries, agents, and operators used to monitor internal and external facing services
• Explore and implement innovative, AI-driven approaches to anomaly detection, root cause analysis, signal correlation, and operational automation
• Partner with infrastructure, product engineering, finance, and security teams to improve visibility into system health and cost efficiency at scale
• Coach and mentor engineers through career development, performance feedback, and technical leadership, fostering a culture of ownership, collaboration, and high quality execution
• We'd love to hear from you if you have
• Strong understanding of distributed systems, instrumentation best practices, SLO design, and incident response workflows
• Experience driving cost transparency and accountability initiatives, including cost attribution, budgeting, forecasting, and alerting in cloud environments
• While not required, it’s an added plus if you also have
• Experience designing or evolving company-wide observability standards, shared libraries, and agent/operator-based integrations
• Experience applying AI or machine learning techniques to anomaly detection, root cause analysis, or operational automation
• Familiarity with OpenTelemetry and modern instrumentation frameworks across multiple programming languages
• Experience scaling and mentoring high-performing engineering teams through platform expansion or significant architectural change
• At Figma, one of our values is Grow as you go
• We believe in hiring smart, curious people who are excited to learn and develop their skills
• You may be just the right candidate for this or other roles
• As the Engineering Manager for Observability, you will lead a team of five engineers responsible for shaping the future of visibility and efficiency at Figma
• You’ll define the strategy for instrumentation standards and cost transparency, drive initiatives to optimize observability footprint and spend, and explore innovative AI-driven approaches to anomaly detection and operational automation

Требования

• 4+ years of experience leading infrastructure, observability, or platform engineering teams, with a track record of delivering highly reliable production systems
• Deep hands-on experience with modern observability platforms (e.g., Datadog, OpenTelemetry) across metrics, logs, and distributed tracing
• Demonstrated ability to set technical direction, drive cross-functional alignment (Engineering, Finance, Security), and make sound architectural decisions in complex environments
• Experience building observability, telemetry, data infrastructure, or evaluation systems for AI or machine learning products, including familiarity with LLM traces, prompt and model versioning, classifiers, and offline or online eval workflows
• Background in cost optimization for infrastructure or observability tooling, including vendor negotiations and usage modeling

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