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Manager, Software Engineering - AI Observability

Figma Berlin·$258,000 – $376,000

Primary stack

AIDatadogOpenTelemetryPrometheusLogstash

Nice to have's

AI

Job description

About the Position

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!

As the Engineering Manager for Observability, you'll lead the team building the systems that show Figma how its platform and its AI products actually behave in production. That spans our core observability stack, meaning metrics, logs, and distributed tracing, as well as a fast-growing new frontier: the AI observability pipeline that turns traces, conversations, and model outputs into the classification and evals that make Figma's AI features measurably better. You'll set strategy across both, raise the bar on instrumentation and data quality, and push into AI-driven approaches to anomaly detection and operational automation. Observability was an unowned space at Figma until recently, so this is a rare chance to shape an early-stage, high-leverage platform that every engineering team here depends on.

This is a full-time role that can be held from one of our US hubs or remotely in the United States.

Responsibilities

  • Lead and grow a 6 engineer team responsible for the reliability, scalability, and evolution of Figma's observability and AI observability platforms.
  • Own and evolve the AI observability ecosystem: a privacy-safe telemetry pipeline that aggregates trace, conversation, and model data, runs classification, and lets teams run evals to measure and improve AI feature quality.
  • Own Figma's core observability stack, including platforms like Datadog, ensuring high availability, strong data quality, and a healthy signal-to-noise ratio across metrics, logs, and traces.
  • Set the technical strategy for the instrumentation standards, libraries, agents, and operators that monitor services across the company.
  • Explore and ship AI-driven approaches to anomaly detection, root cause analysis, signal correlation, and operational automation.
  • Partner across infrastructure, product engineering, finance, and security to give teams clear visibility into system health at scale, including cost efficiency as the team's scope grows.
  • Coach and develop engineers through career growth, feedback, and technical leadership, building a culture of ownership and high-quality execution.

Requirements

  • 4+ years of experience leading and growing engineering teams in infrastructure, observability, platform, or AI systems, with a track record of delivering reliable production systems at scale.
  • A strong foundation in distributed systems and a platform mindset: you build systems other teams adopt and rely on, not just for your own team.
  • Hands-on depth in observability, AI systems telemetry, or both, whether that means metrics, logs, and distributed tracing, or the traces, classification, and evals that power AI products.
  • Fluency with the modern tooling in your area, such as Datadog, OpenTelemetry, and Prometheus, or LLM tracing, prompt and model versioning, and eval workflows.
  • A high operational bar (instrumentation and data quality, SLO design, incident response) and the ability to set technical direction and drive cross-functional alignment in complex environments.

Nice to Have

  • Breadth across both classic observability and AI observability, or the curiosity to grow into whichever is newer to you.
  • Experience creating AI Telemetry-assisted improvement feedback loops for services, in particular for AI products and features.
  • Experience improving infrastructure efficiency, including cost attribution, forecasting, vendor negotiation, and usage modeling.
  • A track record designing company-wide observability standards, shared libraries, and agent or operator-based integrations.
  • Experience applying AI or machine learning to anomaly detection, root cause analysis, or operational automation.
  • Experience scaling and mentoring high-performing teams through platform expansion or major architectural change.

We Offer

  • Competitive salary range: $258,000 - $376,000 USD
  • Equity
  • Comprehensive benefits package including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off.
  • Paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws.
  • Flexible PTO for exempt employees.
  • Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts.
  • Sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles.

About the Company

Figma is dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to [email protected].

© Figma Berlin. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

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