Job description

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. What you’ll do at Figma: 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. We'd love to hear from you if you have: 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. While not required, it’s an added plus if you also 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. 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. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, 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. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $258,000 — $376,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are 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 accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Requirements

Must-haves

This is a full time role that can be held from one of our US hubs or remotely in the United States.
Lead and grow a 6 engineer team responsible for the reliability, scalability, and evolution of Figma's observability and AI observability platforms.
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.
We'd love to hear from you if you have:
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.
While not required, it’s an added plus if you also 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.
Pay Transparency Disclosure
Examples of accommodations include but are not limited to:
Holding interviews in an accessible location
Enabling closed captioning on video conferencing

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

figmaaillmmachine learninggo

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Parental Leave

Wellness