Staff AI Acceleration Engineer - Dave

The Opportunity

Dave is looking for a Staff AI Acceleration Engineer to define the technical foundation for how AI agents are built, connected to data, and safely deployed across Dave.

This is a highly influential individual contributor role focused on architecture, technical strategy, and platform design. You’ll establish the patterns, standards, and infrastructure that enable teams across the company to build trusted AI agents on governed data. Your work will shape Dave’s AI Agent Factory—the platform that makes AI development repeatable, secure, and scalable.

You’ll partner closely with Data Engineering, which owns the trusted data platform, while you design the AI infrastructure that connects large language models to that data through robust governance, semantic consistency, and reusable developer tooling.

Reports to: Director, Data Platform & AI Acceleration

What You’ll Build

• Define the architecture and technical strategy for Dave’s AI Agent Factory, including reusable frameworks, evaluation patterns, deployment standards, and observability.
• Design the MCP server architecture and AI-ready data access layer that enables LLMs to securely reason over governed enterprise data.
• Architect integrations between AI agents and Dave’s semantic layer so business definitions remain consistent across analytics, reporting, and AI experiences.
• Establish governance-by-design patterns for authentication, authorization, auditability, PII protection, and responsible AI deployment.
• Design evaluation frameworks that measure agent quality, reliability, and operational performance before production deployment.
• Partner across Engineering, Data, Security, and Product to establish technical standards that enable AI adoption across the organization.

The Impact

Your work will become the foundation every engineering team builds on as Dave scales AI across the business. By creating trusted infrastructure instead of one-off solutions, you’ll help accelerate development while ensuring AI systems remain reliable, secure, and aligned with our data platform.

What We’re Looking For

Required

• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Information Systems, or a related technical field.
• 8+ years of experience in software engineering, platform engineering, data engineering, ML infrastructure, or AI engineering.
• Experience architecting and delivering production-grade AI platforms, LLM-powered applications, or autonomous agent systems.
• Deep experience designing systems that securely connect LLMs to structured enterprise data through APIs, semantic layers, retrieval systems, or governance frameworks.
• Experience designing MCP servers, function-calling frameworks, tool-use architectures, or similar AI connectivity patterns.
• Strong software engineering fundamentals with expertise building scalable, reliable distributed systems.
• Experience with modern data platforms and infrastructure including Snowflake, dbt, Airflow, Kafka, Python, Kubernetes, and cloud-native technologies.
• Experience establishing engineering standards for testing, monitoring, CI/CD, observability, and operational excellence.
• Demonstrated ability to influence technical direction across multiple teams without direct authority.

Nice to Have

• Experience designing AI evaluation frameworks and automated quality measurement.
• Experience with semantic layer technologies such as dbt Metrics, LookML, or similar platforms.
• Experience building internal developer platforms adopted across engineering organizations.
• Experience within fintech, banking, healthcare, or other regulated industries.
• Experience with data lineage, governance, audit, or compliance automation systems.