Description
At Capital One, we are creating responsible and reliable AI systems, changing banking for good.
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life.
Responsibilities:
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
- Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
- Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance , scalability, cost, latency, throughput , of large scale production AI systems.
- Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
- Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale.
- Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide.
- Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture.
- Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership.
Basic 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, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies.
- At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java.
Preferred Qualifications:
- Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy.
- 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
- Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level.
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Experience in building agentic AI systems and agentic workflows.
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production.
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
- Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership.
- Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance.
- Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams.
- Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact.
- Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).
Salary Information:
- The minimum and maximum full-time annual salaries for this role are:
- Cambridge, MA: $314,800 - $359,300
- McLean, VA: $314,800 - $359,300
- New York, NY: $343,400 - $392,000
- Richmond, VA: $286,200 - $326,700
- San Francisco, CA: $343,400 - $392,000
- San Jose, CA: $343,400 - $392,000