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Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
We are seeking a highly experienced AI Automation Lead with 8+ years of engineering experience to bridge the gap between sophisticated data ecosystems and high-performance user applications. This role is responsible for architecting and delivering our multi-agent AI strategy—moving beyond simple chatbot implementations to autonomous, stateful workflows that solve complex, real-world business problems.
This individual operates as a true full-stack product engineer, equally comfortable working across frontend, backend, data orchestration, and AI systems. You will define the technical vision for AI-driven automation, ensuring solutions are scalable, production-grade, and highly available.
What you’ll do:AI Architecture & Agentic Workflows
Design and implement multi-agent AI workflows that enable coordinated task execution across systems (e.g., fraud detection, risk assessment, financial modeling)
Build human-in-the-loop systems that allow users to monitor and intervene in automated processes
Integrate Snowflake Cortex for in-database AI workloads, including LLM functions, vector search, and ML processing
Full-Stack Engineering
Develop complex, data-rich user interfaces using React to visualize and control AI workflows
Build scalable backend services in Python with a focus on performance, concurrency, and clean API design
Orchestrate workflows and automation pipelines using Apache Airflow
Data & Infrastructure Strategy
Leverage Snowflake and dbt to ensure clean, governed, and high-performance data pipelines
Maintain infrastructure as code and CI/CD pipelines to enable reliable and rapid deployments
Optimize performance and cost of LLM usage and internal AI systems
Technical Leadership
Lead architectural decisions and set engineering standards across the team
Conduct code reviews, mentor engineers, and promote a culture of ownership
Partner with Product to translate business problems into scalable automation solutions
8+ years of professional software engineering experience
Strong expertise in React with the ability to build complex, stateful UIs from scratch
Deep expertise in Python, including async programming and AI/ML frameworks
Experience building multi-agent systems or complex AI workflows (e.g., LangGraph, CrewAI, AutoGen, or similar)
Hands-on experience with Snowflake, including data modeling and AI integrations
Strong experience with Apache Airflow for workflow orchestration
Working knowledge of CI/CD pipelines and containerization (Docker, Kubernetes)
Proven ability to lead technical design and own end-to-end system delivery
Experience with Snowflake Cortex or in-database AI processing
Experience fine-tuning or deploying custom ML models
Background in fintech, risk, fraud, or financial systems
Experience migrating manual processes into automated AI-driven systems
Strong system design experience in distributed, production environments
You are a full-stack AI systems architect who thrives on building end-to-end solutions—not just components. You move beyond traditional CRUD applications and focus on delivering intelligent, automated systems that solve meaningful business problems.
You take ownership of both the system and the user experience, ensuring that AI capabilities are not only powerful but usable and scalable. You can take an ambiguous goal—like automating a fraud review process—and turn it into a fully functional, multi-agent system with a robust user interface in a matter of weeks.
