Data Platform Engineer

About Us:

webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI.

About the Role:

We are looking for a Data Platform Engineer to design and build the connective tissue between real-world data systems and our AI platform. You will create scalable, reusable data connectors and transformation layers that make heterogeneous data sources usable for downstream inference. This role sits at the intersection of distributed systems, data infrastructure and applied AI. This role will act in terms of platform primitives, not pipelines.

Key Responsibilities:

• Design and build robust connectors across SQL / NoSQL databases, APIs (REST / GraphQL), SaaS platforms (e.g., CRM, storage systems)
• Interpret and model heterogeneous source schemas
• Transform raw source data into formats optimized for AI inference
• Work closely with ML, applied AI and forward deployed teams to define feature expectations
• Collaborate with infrastructure teams to design and ship hosted data pipelines
• Optimize for latency, consistency, and edge constraints
• Design resilient ingestion patterns for unreliable or rate-limited systems
• Build logging, monitoring and debuggability into all integrations

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Proven experience building connectors against enterprise systems (SQL/NoSQL databases, Salesforce, S3, REST/GraphQL APIs)
• Systems instinct to architect a platform primitive, not a one-off integration
• Familiarity with inference pipelines or ML-adjacent data preparation preferred
• Comfortable working in a startup environment with ambiguity and evolving requirements

Benefits:

• Competitive salary
• Equity options
• 401k match
• Comprehensive health, dental, and vision benefits package.
• $200/mos Health and Wellness Stipend
• Continuing Education support
• Free parking, for in-office employees
• Flexible time off
• Parental, Bereavement Leave
• Supplemental Life Insurance