AI Engineer, Sr. (Remote)

About The Company Capital One is a leading financial services company dedicated to transforming banking through innovative technology and responsible AI solutions. With a strong commitment to leveraging machine learning and artificial intelligence, Capital One has established itself as an industry pioneer in delivering personalized, real-time customer experiences. The company’s substantial investments in cutting-edge technology infrastructure and top-tier talent enable it to stay at the forefront of AI-driven financial services. Capital One’s mission is to enhance customer satisfaction by simplifying banking processes, detecting unusual charges promptly, and providing intelligent support through advanced AI applications. The organization fosters a culture of innovation, collaboration, and continuous learning, aiming to redefine the future of banking with responsible and scalable AI systems.

About The Role We are seeking a highly experienced Senior Staff AI Engineer to join our dynamic team, with the flexibility of being remote eligible. In this pivotal role, you will lead the development and deployment of advanced AI systems that influence the way Capital One serves its customers and internal stakeholders. You will collaborate with cross-functional teams including research scientists, engineers, product managers, and technical program managers to design, build, and optimize scalable AI solutions. Your expertise will drive innovation in foundation model training, large language model inference, multi-agent workflows, and AI governance. You will play a key role in shaping the technical vision and long-term roadmap of our AI infrastructure, ensuring the integration of the latest research breakthroughs into reliable, high-performance production systems. Additionally, you will establish standards for AI safety, transparency, and performance, and mentor the next generation of AI technical leaders within the organization. This role offers a unique opportunity to influence enterprise-wide AI architecture and contribute to transformative projects that impact millions of customers and internal users.

Qualifications

• Bachelor’s Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies
• Master’s Degree in relevant fields plus at least 8 years of experience in AI/ML development
• Proficiency in programming languages such as Python, Go, Scala, CUDA, or Java with a minimum of 10 years of experience
• Experience architecting AI platforms with considerations around cost, latency, throughput, and accuracy
• Proven track record in deploying scalable AI solutions on cloud platforms like AWS, Google Cloud, Azure, or private clouds
• Strong leadership skills with experience mentoring engineering teams and influencing cross-functional stakeholders up to SVP level
• Deep understanding of AI and ML algorithms, including LLM inference, similarity search, vector databases, guardrails, and memory systems
• Knowledge of optimizing training and inference software for hardware utilization, latency, throughput, and cost efficiency
• Experience designing long-term AI infrastructure strategies balancing ethical, regulatory, and business considerations
• Excellent communication and presentation skills, capable of articulating complex AI concepts to diverse audiences
• Recognized leadership in applied AI through patents, publications, or open-source contributions

Responsibilities

• Partner with cross-disciplinary teams to deliver AI-powered products that enhance customer and associate interactions with Capital One
• Design, develop, test, deploy, and support AI components including foundation models, large language models, multi-agent workflows, and governance frameworks
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch to build scalable solutions
• Invent and implement state-of-the-art optimization techniques for foundation models to improve performance metrics like scalability, cost, latency, and throughput
• Contribute to the technical vision and strategic roadmap for enterprise AI systems, ensuring alignment with business objectives
• Define and steer AI architecture standards, integrating research breakthroughs into production environments with reliability and scalability
• Lead initiatives to establish AI safety, transparency, and…