Manager, Software Engineering - AI Observability
Posted by employer 8 months ago
First seen on Joblaze 6 months ago
Last verified on the company career page 14 hours ago
Skills & Technologies
Requirements
- Experience
- 4+ years
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze summary
In the role of Engineering Manager for Observability at Figma, the individual will lead a team focused on enhancing the reliability and efficiency of the company's observability systems. Key responsibilities include defining instrumentation standards, optimizing cost transparency, and implementing AI-driven solutions for operational challenges. This position is ideal for a seasoned leader with a strong background in distributed systems and a passion for cross-functional collaboration. Figma's commitment to innovation and teamwork underscores the importance of this role in shaping the future of design and collaboration.
Joblaze insights
- Listed about 6 months ago — first seen on Joblaze April 14, 2026. Last confirmed on Figma's careers page October 29, 2026.
- Salary band is above the typical range for Management roles (median ~$170,000).
- Starts above 95% of 20 comparable lead management roles in United States that list AI we track (median $174,843 across 12 companies). See AI salary trends
- AI appears in 5.2% of 611 comparable lead management roles in United States; Datadog appears in 0.5% of 611 comparable lead management roles in United States.
Quick facts
- Is the Manager, Software Engineering - AI Observability role remote?
- It's hybrid — Figma expects some on-site time in San Francisco, CA • New York, NY • United States.
- What's the salary range?
- Figma lists $258,000–$376,000 for this role.
- How much experience is required?
- At least 4 years of relevant experience for this Manager, Software Engineering - AI Observability role.
- Where is the role based?
- Figma is hiring for this position in San Francisco, CA • New York, NY • United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, Datadog, Machine Learning, OpenTelemetry.
- What seniority level is this role?
- Figma targets lead candidates for this position.
- Is this full-time or contract?
- Full-time for this Manager, Software Engineering - AI Observability role at Figma.
From the original posting
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.
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.
Pay Transparency Disclosure
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.
Standard company text repeated across Figma's postings is omitted here.