Flatfile is revolutionizing enterprise data handling through AI automation. We're building an AI-native data mapping, cleaning, and transformation platform that tackles the most stubborn data problems for the world's largest organizations.
You’ll work at the intersection of conventional software engineering and machine learning, focusing on applying AI to solve real-world problems rather than fundamental ML research.
As James Brady from Elicit notes: "If you're a software engineer who relishes the more difficult parts of backend code—like concurrency, fault-tolerance, and distributed systems—you could be a great AI engineer."
This role reports to: Jon Bell, VP of Product
You'll own critical parts of our AI-powered data platform
Design and implement robust backend services that integrate with various AI models for data understanding and transformation
Build fault-tolerant systems that can handle the high latency and variance inherent in working with large language models
Create streaming architectures for real-time AI processing of customer data
Develop evaluation frameworks to measure and improve our AI features' accuracy and reliability
Work closely with our product team to prototype and ship new AI capabilities
Help learn and establish best practices for AI development at Flatfile
You’ll also get to write some good old-fashioned code and ship more traditional software features too :)
Oh, and we all fix bugs
Our tech stack
In this role, you’ll use LangGraph, various LLMs and open source models, React, Typescript, our in-house design system Baseline, Node (Nest.js), Prisma, Postgres, Git, Flatfile’s homegrown data engine, and utilize AI for performance gains on a daily basis.
Essential
• Experience building production backend systems
• Strong computer science fundamentals, especially in distributed systems
• Experience handling asynchronous workflows and building resilient services
• Genuine enthusiasm for AI technology and its practical applications
• Track record of shipping customer-facing features
Great to have
• Experience working with LLMs in production environments
• Background in data processing or ETL systems
• Familiarity with AI model deployment and optimization
• Experience with streaming architectures
• Open source contributions to AI/ML tools
• A chance to shape the future of enterprise data automation
• A highly collaborative, fast-paced engineering culture
• Ownership of significant technical challenges and no PM overlords
• The opportunity to work with cutting-edge AI technology
• Competitive compensation and equity
• A team of humble and audacious builders who take pride in their work
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