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About the Role

At Capital One, we are creating responsible and reliable AI systems to change banking for good. We are at the forefront of enterprises leveraging AI, bringing humanity and simplicity to banking through AI & ML applications. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses.

Responsibilities

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
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.
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.
Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems.
Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards.
Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity.

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies.
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy.
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
Experience designing, developing, delivering, and supporting complex AI systems.
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.
Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines.
Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes.
Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression.
Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).

Skills

AI
ML
Foundation model training
Large language model inference
Agents and multi-agent workflows
Similarity search
Guardrails
Model evaluation
Experimentation
Governance
Observability
AWS Ultraclusters
Huggingface
VectorDBs
PyTorch
Python
Go
Scala
CUDA
Java
C++
C#
Golang
Cloud platforms (AWS, Google Cloud, Azure)
Agentic AI systems
Heterogeneous AI systems
Ethical AI deployment
Explainability
Fairness
Human-in-the-loop review processes
Model compression
Dynamic inference strategies

Location

Cambridge, MA
McLean, VA
New York, NY
San Francisco, CA
San Jose, CA

Work Type

Full-time

Experience Level

6 years of experience
4 years of experience
7 years of experience

Education Level

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Salary/Compensations

Cambridge, MA: $229,900 - $262,400
McLean, VA: $229,900 - $262,400
New York, NY: $250,800 - $286,200
San Francisco, CA: $250,800 - $286,200
San Jose, CA: $250,800 - $286,200

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One Financial is made up of several different entities.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.