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FigmaTranslationLeadershipLLMs
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 67 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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✓
What Figma INC paid sponsored hires in similar roles1 certified filing for “Manager, Software Engineering” (Computer and Information Systems Managers) in NY: $295k–$295k, median $295k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 67 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Figma INC paid sponsored hires in similar roles
- 1 certified filing for “Manager, Software Engineering” (Computer and Information Systems Managers) in NY: $295k–$295k, median $295k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
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 Design Systems Adherence, you'll lead the team building the workflows, tools, and quality feedback loops that help customers create design and code that correctly adheres to their design system when working with Figma’s Agents. This work spans context engineering i.e making guidelines, examples, and documentation useful to AI, agent architecture improvements as well as creating datasets, evaluators, and benchmarks that show how well outputs follow a customer's design system. You'll set strategy across these areas, raise the bar on adherence measurement, and turn evaluation results and customer feedback into feedback loops that make design quality better.
This is a high-impact opportunity to shape Figma's Agent and improve overall design quality. An organization’s Design System is one of the key differentiators of design quality as we can use it to make agent output adhere to their specific brand, products and design language. We are also aiming to solve Design <> Code parity and minimize drift away from the defined design system in both code and designs.
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 6-8 engineer team responsible for Design Systems Adherence across our workflows
• Coach and develop engineers through career growth, feedback, and technical leadership, building a culture of ownership and high-quality execution
• Own and evolve design system context: make guidelines, examples, documentation, and other guidance available to AI as useful, actionable context that improves how it applies a customer's system
• Set the technical strategy for adherence measurement - including high-fidelity evaluation datasets, quality rubrics, evaluators, and deterministic regression checks that catch issues as Figma's Agent evolves
• Build benchmarking, tools, and dashboards that help Figma and customers understand design system adherence and act on the results, while tracking visual quality, latency, and cost
• Partner closely with Product, Design, and AI Research teams at Figma to achieve business impact
We'd love to hear from you if you have:
• 3+ years of experience leading and growing high-impact engineering teams with a track record of strong impact
• Hands-on depth in building AI assistants, evaluation systems, and using the latest large language models and harnesses
• Fluency with modern AI development and evaluation workflows, such as context management, dataset curation, automated evaluators, benchmarking, and regression testing
• A strong foundation in software engineering and a platform mindset: you build tools and systems other teams adopt and rely on, alongside workflows that solve real customer problems
• A high quality bar for customer experience, data quality, and reliable measurement, 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:
• Strong understanding of design systems, including components, tokens, usage guidelines, and their integration across design and code
• Proven ability to establish evaluation and customer feedback loops to continuously improve AI products
• Skilled in benchmarking AI p
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