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We built it. You make it. A radically simple, affordable and personalizable truck (or SUV, your call).
Senior Backend Engineer, AI
Location
United States + 53 moreAll locations: United States | Canada | South Africa | Egypt | Algeria | Angola | Benin | Botswana | Burkina Faso | Burundi | Cameroon | Cabo Verde | Central African Republic | Chad | Congo | Côte D'ivoire | Democratic Republic of the Congo | Equatorial Guinea | Eritrea | Ethiopia | Gabon | Gambia | Ghana | Guinea | Guinea-bissau | Kenya | Lesotho | Liberia | Libya | Madagascar | Malawi | Mali | Mauritania | Mauritius | Mayotte | Morocco | Mozambique | Namibia | Niger | Nigeria | Réunion | Rwanda | Senegal | Seychelles | Sierra Leone | Somalia | Sudan | Eswatini | Tanzania | Togo | Tunisia | Uganda | Zambia | Zimbabwe
Posted
119 days ago
Salary
$95K - $200K / year
Seniority
Senior
No structured requirement data.
Job Description
Senior Backend Engineer, AI
Slate Auto
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Slate's product already uses AI across the stack - background removal, active speaker detection, auto-captioning, content suggestions, and image generation - but each integration was built ad hoc. We're looking for someone to level up our AI stack, turning a collection of API calls into an actual platform: a shared AI services layer that any team can build on without reinventing the plumbing every time. These services will power explosive growth in our capabilities and our customer base. You'll own the infrastructure that sits between our product and the models - orchestration across providers like OpenAI and Anthropic, prompt and pipeline management, evaluation and quality gating, cost controls, and observability. The goal is to make it trivially easy for any engineer at Slate to ship and evaluate AI-powered features that are reliable, fast, and cost-efficient in production. This is a senior backend role with an AI focus, not an ML research role. You won't necessarily be training models - but you will be building the systems that make external models useful at scale. What You'll Actually Do - Build Slate's AI services platform - Design and implement a shared services layer for AI capabilities across the product. - Own model integration and provider strategy - Build evaluation and quality pipelines - Optimize cost and performance at scale - Shape technical direction Qualifications - 7+ years of backend development, with strong TypeScript/Node.js skills - Experience building and operating AI/ML infrastructure or platform services in production - Deep understanding of LLM APIs, vision models, and media processing pipelines - Track record of designing systems for reliability, observability, and cost efficiency - Familiarity with prompt engineering, evaluation frameworks, AI output quality measurement and A/B testing Requirements - Built abstraction layers over multiple AI/ML providers with failover and routing logic - Designed APIs and services that other engineering teams consume as internal platform - Implemented caching, batching, or queue-based patterns to manage API costs at scale - Instrumented production AI systems with meaningful metrics beyond basic latency/errors - Worked with image generation, vision models, video analysis, or media processing in a product context - Bonus: Python experience for ML tooling, data pipelines, or model evaluation Benefits - Equity options - Unlimited PTO (we actually take it) - $200/month wellness stipend - Health insurance stipend - Home office budget Company Description Slate is the creative workspace for brand social teams. We help teams create and ship on-brand content fast with an all-in-one editor, built-in asset management, and seamless creative file workflows, backed by hands-on support from people who have done the job. Teams across top sports leagues and global brands like Amazon and Hoka use Slate every day to elevate their social presence.
Job Requirements
- 7+ years of backend development, with strong TypeScript/Node.js skills
- Experience building and operating AI/ML infrastructure or platform services in production
- Deep understanding of LLM APIs, vision models, and media processing pipelines
- Track record of designing systems for reliability, observability, and cost efficiency
- Familiarity with prompt engineering, evaluation frameworks, AI output quality measurement and A/B testing
- Built abstraction layers over multiple AI/ML providers with failover and routing logic
- Designed APIs and services that other engineering teams consume as internal platform
- Implemented caching, batching, or queue-based patterns to manage API costs at scale
- Instrumented production AI systems with meaningful metrics beyond basic latency/errors
- Worked with image generation, vision models, video analysis, or media processing in a product context
- Bonus: Python experience for ML tooling, data pipelines, or model evaluation
Benefits
- Equity options
- Unlimited PTO (we actually take it)
- $200/month wellness stipend
- Health insurance stipend
- Home office budget
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