About Eventual

Every breakthrough AI application—from foundation models to AI agents to autonomous vehicles—requires processing massive amounts of images, video, and complex data. But here's the problem: today's data platforms (Databricks, Snowflake, etc) are built on top of tools made for spreadsheet-like business analytics and SQL queries, not petabytes of multimodal information. This forces teams to waste months building complex infrastructure instead of solving the problems that are core to their business.

Our cofounders started Eventual in 2022 out of frustration with this exact challenge. Our mission is simple: make querying any type of data—images, video, audio, text—as intuitive as working with tables, yet powerful enough to handle petabytes at production scale. Unlike traditional engines with hardcoded operations, we handle the chaos of real production: coordinating with dozens of external APIs, managing GPU clusters, and turning the 0.1% failure rate that kills traditional systems into reliable execution. Our open-source engine Daft already powers critical AI workloads at companies such as Amazon, Mobileye, TogetherAI, and CloudKitchens, running on 800,000 CPU cores daily.

We've assembled a world-class team from Databricks, AnyScale, Tesla, and Lyft with deep expertise in high-performance computing and big data infrastructure. Backed with significant funding from YCombinator, Caffeinated Capital, Array.vc, and top angels from Databricks, Anthropic, Meta, and Lyft, we're building the generational technology that will enable entirely new classes of AI breakthroughs. We’re in the process of doubling our team, join us today!

Your Role

As our AI Developer Advocate, you will champion AI workload use-cases and drive adoption of Daft, our distributed query engine for multimodal data. You'll work directly with users to build compelling end-to-end demonstrations that showcases Daft as the definitive engine for any modality of data at any scale, turning complex multimodal scenarios into accessible, reproducible examples. When you're not producing amazing developer facing content, your work will also directly influence Daft's roadmap as you learn from our users.

Key Responsibilities

• User Engagement: Work closely with users to understand multimodal data challenges and translate them into compelling use-cases

• Technical Content Creation: Develop tutorials, videos, and technical demos showcasing things like:

  • Data Ingest for Multi-modal RAG systems that seamlessly query documents, images, videos, and code repositories for AI assistants

  • Agent data orchestration enabling AI agents to access and reason over massive unstructured data repositories

  • Foundation model training pipelines preparing clean, multimodal datasets for LLM and vision model training

  • Multi-modal generation workflows combining text, image, and video generation with complex data dependencies

  • Real-time AI assistant data ingestion processing user documents, conversations, and media for personalized AI experiences

• Community Building: Present at conferences, meetups, and technical events to grow our developer community

• Product Development: Drive feature requirements and improvements for our open-source project based on user feedback and real-world applications

What We Look For

• Strong background in AI/ML and multimodal data processing

• Experience with distributed systems and data engineering

• Proven track record creating technical content and speaking at events

• Ability to translate complex technical concepts into clear, actionable guidance

• Open-source contribution experience preferred

Perks & Benefits

• Hybrid work environment - 3x a week in office

• Competitive comp and startup equity

• Catered lunches and dinners for SF employees

• Commuter benefit

• Team building events & poker nights

• Health, vision, and dental coverage

• Flexible PTO

• Latest apple equipment

• 401k plan with match!