Staff Full Stack Engineer

SoFi

7d•$153,600 - $264,000

About The Position

As a Staff Full Stack Engineer, you will serve as a cornerstone of technical leadership, driving the ideation, architectural design, and optimization of enterprise-scale, full-stack ecosystems. We are seeking a visionary with 8+ years of engineering depth and a proven track record of delivering complex, end-to-end solutions. In this role, you will bridge the gap between high-level business strategy and technical execution, championing engineering excellence while serving as a pivotal mentor and subject matter expert to the broader engineering organization.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a strictly related technical discipline.
8+ years of robust software engineering experience, with a specialized focus on architecting full-stack AI-driven product ecosystems.
A distinguished track record of delivering production-grade, highly available cloud services that operate reliably at enterprise scale.
Advanced proficiency in the React and Node.js ecosystems, with a mastery of seamless front-to-back-end integration for bespoke enterprise applications.
Extensive hands-on experience with modern database platforms—Snowflake preferred—including the utilization of Snowflake Cortex and advanced AI/ML integration patterns.
Deep expertise in designing and managing complex real-time and scheduled data pipelines using Apache Airflow.
Comprehensive experience in Infrastructure as Code (IaC) and environment management, utilizing ArgoCD and GitLab CI/CD to drive automated, resilient deployment strategies.
Committed to the growth of the engineering organization through active mentorship, fostering a high-performance culture, and elevating the technical caliber of the team.
A relentless advocate for engineering rigor, consistently challenging the status quo to drive continuous improvement in code quality and architectural standards.
Exceptional communication skills with the ability to bridge technical and non-technical domains, driving consensus and decision-making among diverse stakeholders.
A proactive leader who takes end-to-end ownership, champions a culture of innovation, and builds influential partnerships across the broader engineering community.

Nice To Haves

Direct experience deploying and scaling production-level Generative AI solutions, specifically LLM-powered agents or Retrieval-Augmented Generation (RAG) architectures.
Previous background in Fintech or high-throughput consumer-facing environments, with an understanding of the unique security and regulatory nuances involved.
Advanced experience with AWS ecosystem services and a broad familiarity with modern cloud-native orchestration platforms.
A sophisticated understanding of latency, throughput, and scalability trade-offs, with the ability to optimize complex distributed systems for performance.
Strong conceptual mastery of diverse programming paradigms, including Object-Oriented (OOP) and Functional Programming, to ensure clean, maintainable, and modular codebases.
Experience navigating and integrating emerging AI workflow orchestration tools and third-party AI research platforms.

Responsibilities

Architect and deploy sophisticated, end-to-end applications, leveraging deep expertise in interactive interfaces and complex data integration—including the orchestration of AI-native database functions like Snowflake Cortex.
Partner with AI specialists to architect multi-agentic systems, implementing autonomous, stateful workflows designed to solve high-consequence, real-world business challenges.
Design and automate high-performance real-time and batch data pipelines using enterprise orchestration tools such as Apache Airflow, ensuring seamless data liquidity across the stack.
Standardize deployment lifecycles and cloud infrastructure by implementing GitOps methodologies via ArgoCD, GitLab CI/CD, and AWS best practices.
Deploy and tune complex business process engines within enterprise frameworks, ensuring maximum reliability, scalability, and observability.
Lead the translation of ambiguous product requirements into rigorous technical specifications, overseeing the entire execution lifecycle from initial ideation to post-deployment optimization.
Act as a technical bridge between Product, Design, and Engineering to deliver member-centric solutions while fostering a culture of continuous learning and growth.
Drive engineering rigor through comprehensive code and design reviews, serving as a final decision-maker for critical architectural choices and software standards.
Maintain a cutting-edge pulse on GenAI, LLM infrastructure, and emerging tooling; proactively translating industry trends into actionable product roadmaps and enhanced technical capabilities.