Staff AI Software Engineer, Risk Engineering

SoFi-posted 8 days ago

Full-time • Mid Level

Seattle, WA

1,001-5,000 employees

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The role: As a Staff Software Engineer focused on Gen AI applications, you’ll play a critical, hands-on role in building, deploying, and optimizing scalable, real-time, full-stack custom applications powered by the latest advances in Generative AI. The ideal candidate has 8+ years of engineering experience, a proven record of full-stack delivery, and deep expertise in designing AI-driven solutions from the UI to the data back-end. You will work across cross-functional delivery teams to shape technical architecture, champion best practices, and directly produce high-value solutions for our users.

Architect, design, and build end-to-end user-facing AI applications using rich interactive user-interfaces with your expertise working with information extracted from databases and APIs (including leveraging Snowflake Cortex for advanced AI workloads).
Manage deployment pipelines and infrastructure as code using ArgoCD, GitLab CI/CD, and AWS best practices.
Design and implement multi-agentic AI applications leveraging frameworks like LangChain / LangGraph, enabling autonomous, stateful, and collaborative agent workflows for complex, real-world problem solving
Own technical decompositions of new product requirements; lead delivery from ideation to deployment and continual improvement.
Deploy, optimize, and monitor workflows on enterprise frameworks
Automate real-time and batch data flows using orchestration tools such as Apache Airflow.
Participate in technical architecture reviews, code and design reviews, and help guide technical decision-making for AI-driven services.
Collaborate with Product, Design, and Engineering to deliver high-impact solutions; mentor peers and foster a growth-mindset environment.
Stay current with GenAI, LLM infrastructure, and the evolving tooling ecosystem; generate ideas to expand product capabilities and technical reach.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
8+ years of professional software engineering experience, with heavy focus on full-stack custom product delivery specializing in AI
Solid devops and infrastructure-as-code experience using ArgoCD and GitLab for deployment, CI/CD, and environment management.
Advanced proficiency in React, Node.js, and front-end–to–back-end custom app development.
Extensive hands-on experience with database platforms - Snowflake strongly preferred, including advanced features, AI/ML integrations, and Snowflake Cortex.
Deep expertise in orchestrating real-time and scheduled pipelines with Airflow.
Track record of delivering high-quality, production-grade, scalable, and highly available cloud-based services.
Strong communicator; able to collaborate and drive decision-making with cross-functional stakeholders.
Willingness to take ownership, mentor others, and champion learning and innovation within the organization.

Exposure to other cloud-native or AI workflow orchestration platforms.
Prior fintech or high-throughput consumer product experience.
Experience deploying and scaling LLM-powered chatbots or retrieval-augmented generation (RAG) platforms.

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