Lead/Staff AI Acceleration Engineer

\u003ch2>\u003cstrong>Dave vs. Goliath. We’re Dave.\u003c/strong>\u003c/h2>\u003cp>Dave is a financial app on a mission to build products that level the financial playing field. It is redefining the financial landscape by leveraging technology to create an affordable, transparent, and user-centric access to liquidity for millions of Americans. As a leading innovator in the U.S. financial services sector, Dave’s digital financial platform offers products designed to meet the credit needs of those underserved by traditional financial institutions. Dave’s offerings include its flagship ExtraCash product, providing members up to $500 in short-term advances within minutes. The company is on track to launch several new product offerings in 2026, including a Buy Now Pay Later (BNPL) option.\u003c/p>\u003cp>Dave is focused on serving Americans who are financially vulnerable or living paycheck to paycheck. Dave is leading the charge in creating a new era of credit products that prioritizes speed, affordability, and accessibility, making it the go-to financial partner for those who need it most.\u003c/p>\u003cp>Dave is on a mission to build financial products that level the playing field. We serve millions of Americans who have been overlooked by traditional systems, giving them faster, more transparent access to liquidity when they need it most.\u003c/p>\u003cp>We’re hiring a Lead / Staff AI Acceleration Engineer to help define how AI is built and used across Dave.\u003c/p>\u003ch2>\u003cstrong>The Opportunity\u003c/strong>\u003c/h2>\u003cp>This is a foundational role on the AI Acceleration team. You’ll help shape the systems that power how AI agents are created, connected to data, and safely deployed across the company.\u003c/p>\u003cp>Your focus is not just building individual solutions. You’ll create the underlying infrastructure and patterns that allow teams across Dave to build and trust AI-driven workflows. Early work centers on analytics automation — agents that generate insights, detect anomalies, and handle recurring reporting.\u003c/p>\u003cp>You’ll partner closely with Data Engineering, building on a trusted data platform to create an AI Agent Factory that scales across the business.\u003c/p>\u003ch2>\u003cstrong>What You’ll Build and Own\u003c/strong>\u003c/h2>\u003cul>\u003cli>The AI Agent Factory: shared patterns, templates, and infrastructure that make it easy to build and deploy reliable agents\u003c/li>\u003cli>Systems that connect LLMs to structured data safely, including access control, context delivery, and governance\u003c/li>\u003cli>Integrations with the semantic layer to ensure agents and dashboards use consistent business definitions\u003c/li>\u003cli>Evaluation and observability frameworks that help teams understand agent quality and behavior over time\u003c/li>\u003cli>Guardrails that reduce risk, including protections against hallucinations, cost overruns, and data misuse\u003c/li>\u003cli>Early analytics automation agents that teams rely on for insight generation and exploration\u003c/li>\u003c/ul>\u003ch2>\u003cstrong>The Impact\u003c/strong>\u003c/h2>\u003cp>You’ll help establish how AI operates across Dave. When this work is successful, teams move faster with better information — and spend less time waiting on manual analysis.\u003c/p>\u003ch2>\u003cstrong>What We’re Looking For\u003c/strong>\u003c/h2>\u003ch3>Experience / Technical Foundation\u003c/h3>\u003cul>\u003cli>6+ years in data engineering, ML engineering, AI infrastructure, or platform engineering\u003c/li>\u003cli>Hands-on experience building LLM-powered applications, agents, or tool-use systems in production\u003c/li>\u003cli>Experience connecting LLMs to structured data in a safe, reliable way (APIs, data access layers, context delivery, governance)\u003c/li>\u003cli>Strong software engineering fundamentals, including testing, monitoring, and production reliability\u003c/li>\u003cli>Experience with modern data and ML tooling (e.g., Python, Snowflake, dbt, Airflow, Kafka, Kubernetes or equivalents)\u003c/li>\u003cli>Experience operating production systems, including CI/CD, monitoring, and incident response\u003c/li>\u003c/ul>\u003ch3>Bonus\u003c/h3>\u003cul>\u003cli>Experience designing evaluation frameworks for AI systems\u003c/li>\u003cli>Familiarity with semantic layer tools (e.g., dbt metrics layer, LookML)\u003c/li>\u003cli>Experience in fintech or other regulated environments\u003c/li>\u003cli>Experience building internal platforms or developer tooling used across teams\u003c/li>\u003cli>Exposure to data lineage, audit systems, or compliance automation\u003c/li>\u003c/ul>\u003ch2>\u003cstrong>What Makes Someone Successful Here\u003c/strong>\u003c/h2>\u003cp>You take responsibility for outcomes, not just implementation. You think in systems — how agents interact with data, how teams adopt what you build, and how decisions scale across the company. You’re thoughtful about trade-offs and build solutions that hold up ove