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About the Role

As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud. You will work alongside talented developers, AI/ML experts, data analysts, product managers, and people leaders. Distinguished Engineers are leading experts who devise practical, reusable solutions to complex problems, drive innovation, and optimize business outcomes with strong technology solutions. You will promote a culture of engineering excellence, mentor internal talent, and actively recruit to build our community. You will operate as a trusted advisor for key technologies, platforms, and capability domains, sharing knowledge through communications, code samples, and blog posts. In this role, you will collaborate with Capital Markets and Financial Planning Technology teams to drive architectural excellence, establish AI-native engineering standards, and deliver next-generation infrastructure for liquidity management, predictive analytics, and financial planning.

Responsibilities

Articulate and evangelize a bold technical vision for your domain
Decompose complex problems into practical and operational solutions
Ensure the quality of technical design and implementation
Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability
Continue learning and injecting advanced technical knowledge into our community
Handle several projects simultaneously, balancing your time to maximize impact
Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community
Lead proof-of-concept development for emerging AI frameworks and architectural patterns
Collaborate with other Finance Technology towers reviewing architectures and designs outside your immediate domain and contributing a cross-cutting perspective that raises the bar org-wide
Champion AIOps practices — driving platform reliability through AI-assisted anomaly detection, automated remediation, and predictive alerting across the portfolio

Requirements

Bachelor’s Degree
At least 7 years of experience in software engineering and solution architecture
At least 7 years of experience in enterprise architecture and design patterns
At least 7 years of experience in designing and building distributed HPC and ML systems
At least 7 years of experience in full ML development lifecycle using AI and ML frameworks
At least 7 years of experience in cloud computing (AWS, Microsoft Azure, Google Cloud)
At least 7 years of experience in data engineering
Bachelor's or Master's in Computer Science, Applied Mathematics, or a related technical field
10+ years of experience in one or more of: software engineering and solution architecture, enterprise architecture and design patterns, distributed HPC and ML systems, ML development lifecycle, cloud computing, or data architecture
10+ years of hands-on coding in commonly used languages Python, Java, Go, Scala, JavaScript/TypeScript, or similar
8+ years owning the full SDLC, conception through architecture, implementation, testing, deployment, and production support
Demonstrated AI-native engineering practice across all three layers: Daily use of AI coding assistants, Spec/intent driven development, AI embedded in CI/CD and SDLC tooling
Production experience building LLM-backed or agentic systems — prompt engineering, evaluation frameworks, observability, and guardrails included
Experience working directly with quantitative analysts or data scientists — model development lifecycles, feature pipelines, backtesting, ML deployment, and the rigor to validate what a model is actually doing

Skills

Software engineering
Solution architecture
Enterprise architecture
Design patterns
Distributed HPC and ML systems
ML development lifecycle
AI frameworks
ML frameworks
Cloud computing
AWS
Microsoft Azure
Google Cloud
Data engineering
Python
Java
Go
Scala
JavaScript/TypeScript
SDLC
AI coding assistants
Spec/intent driven development
CI/CD
LLM-backed systems
Agentic systems
Prompt engineering
Evaluation frameworks
Observability
Guardrails
Quantitative analysis
Data science
Model development lifecycles
Feature pipelines
Backtesting
ML deployment

Location

Remote
Cambridge, MA
McLean, VA
New York, NY
Richmond, VA

Work Type

Remote Eligible
Full-time

Experience Level

Distinguished Engineer
7+ years of experience
10+ years of experience
8+ years owning the full SDLC

Education Level

Bachelor's Degree
Bachelor's or Master's in Computer Science, Applied Mathematics, or a related technical field

Salary/Compensations

Remote (Regardless of Location): $244,700 - $279,200
Cambridge, MA: $269,100 - $307,200
McLean, VA: $269,100 - $307,200
New York, NY: $293,600 - $335,100
Richmond, VA: $244,700 - $279,200

Benefits

Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

About the Company

Capital One is open to hiring a Remote Employee for this opportunity.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
Capital One promotes a drug-free workplace.
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.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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.