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The Staff Software Engineer will build and optimize GenAI full-stack applications, manage deployment pipelines, and mentor team members while ensuring high-quality solutions and collaboration with cross-functional teams.
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Who we are:
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.
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 9+ 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.
What you’ll do:
- Architect, design, and build end-to-end GenAI-powered applications using rich interactive user-interfaces with your expertise in React, Node.js, working with information from Snowflake (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 LangChain and 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 Generative AI 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.
What you’ll need:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 9+ 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 Snowflake, including advanced features, AI/ML integrations, and Snowflake Cortex.
- Deep expertise in orchestrating real-time and scheduled pipelines with Airflow.
- Demonstrable expertise with AWS SageMaker and Bedrock for developing, training, and deploying machine learning models, especially those involving large language models or generative AI workflows.
- 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.
Nice to have:
- 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.
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.The Company hires the best qualified candidate for the job, without regard to protected characteristics.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.New York applicants: Notice of Employee RightsSoFi is committed to embracing diversity. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email [email protected].Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
Top Skills
Apache Airflow
Argocd
AWS
Aws Sagemaker
Bedrock
Gitlab Ci/Cd
Node.js
React
Snowflake
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