Distinguished Software Engineer - IFX

About the role

The Distinguished Software Engineer - IFX role at Capital One is a technical leadership position aimed at defining the future of banking in the cloud. This role involves working alongside a talented team of developers, machine learning experts, product managers, and people leaders to drive innovation and optimize business outcomes.

Responsibilities

• Architect and build control and data plane implementations required to realize a highly available, multi-tenant, large scale and a secure machine learning platform
• Develop Ray and Spark distributed compute engine solutions to accelerate diverse workloads from LLM pre-training and reinforcement learning to large-scale data processing, while maximizing compute unit economics
• Engineer systemic improvements for operational excellence including automating KTLO (Keep The Lights On) workflows
• Direct the technical execution of a diverse project portfolio, collaborating with developers specializing in distributed microservices to running large foundation models
• Work cross-functionally with product and program management disciplines, and stakeholder and partners across Capital One to help optimize business outcomes while driving towards strong technology solutions
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and leading system design and code review sessions
• Help elevate the Capital One Distinguished Engineering community and establish yourself as a go-to resource on given technologies and technology-enabled capabilities
• Lead the way in creating next-generation talent, mentoring internal talent and actively recruiting external talent to bolster the Capital One tech talent pool

Qualifications

• Bachelor’s Degree
• At least 7 years of experience in software engineering
• At least 7 years of experience designing distributed systems, backend architecture, and API platforms
• At least 5 years of experience with public cloud technologies

Preferred Qualifications

• A Master’s Degree in Computer Science or a Master’s Degree in Software Engineering
• 3+ years of experience building platforms that support LLM training, fine-tuning, or high-throughput inference
• 3+ years of experience with AWS-specific compute primitives (EKS, EC2 UltraClusters, Graviton) and cost-optimization strategies
• 3+ years of experience with building platforms at scale and experience with distributed computing frameworks such as Spark and Ray