Senior AI Software Engineer Manager, Risk Engineering

SoFi•Seattle, WA

10h

About The Position

As a Senior Manager - AI Software Engineer, you will play a critical, hands-on role in managing a high-performing team while building, deploying, and optimizing scalable, real-time, full-stack custom applications, from traditional workflows and user interfaces, to applications powered by the latest advances in AI. You are a seasoned and experienced full-stack engineer with deep expertise in designing and delivering software solutions from the UI to the data back-end. You roll up your sleeves to have a "code first" approach. You will work across cross-functional delivery teams to shape technical architecture, champion engineering best practices, lead technical design, mentor engineers, drive product management engagement, and ensure successful delivery of high-value solutions for our users.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
9+ years of professional software engineering experience, with a heavy focus on full-stack custom product delivery, including experience leading engineering teams, projects, or functions.
Proven track record of simultaneously delivering high-quality, production-grade, scalable, and highly available cloud-based services, and managing project and delivery milestones.
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.
Strong communicator; able to collaborate and drive decision-making with cross-functional stakeholders, including product management.
Willingness to take ownership, mentor others, and champion learning and innovation within the organization.

Nice To Haves

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

Responsibilities

Own the end-end full-stack engineering infrastructure, and drive technical delivery from ideation and requirements decomposition through to deployment and continual improvement, ensuring alignment with product and business goals.
Engage with product, design, and business stakeholders to align technical strategy, drive decision-making, and deliver high-impact solutions.
Architect, design, and build end-to-end user-facing applications using rich interactive user-interfaces.
You will remain hands-on, leveraging your expertise working with information extracted from databases and APIs (including native database functions such as Snowflake Cortex for advanced AI workloads).
Participate in the design and implementation of production-grade, scalable multi-agentic AI applications leveraging frameworks like LangChain / LangGraph, enabling autonomous, stateful, and collaborative agent workflows for complex, real-world problem solving.
Manage deployment pipelines and infrastructure as code using ArgoCD, GitLab CI/CD, and AWS best practices.
Deploy, optimize, and monitor workflows on enterprise frameworks.
Automate real-time and batch data flows using orchestration tools such as Apache Airflow.
Lead code and design reviews, making critical technical decisions for AI-driven services.
Stay current with software engineering, AI, LLM infrastructure, and the evolving tooling ecosystem; generate ideas to expand product capabilities and technical reach.
Lead and mentor a team of talented software engineers, fostering a culture of technical excellence, ownership, and innovation.