Risk Data Engineering, AI Manager

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 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.