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Today

Sr. Staff AI Engineer

Capital One McLean, VA

McLean, VA

Today

$315k - $359k/yr Full time Senior Agents Ai Engineer

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Job Description

Capital One is seeking a Senior Staff AI Engineer to design, build, deploy, and support AI software components and foundational AI systems. This onsite role in McLean focuses on foundation model training and inference, agent workflows, search, guardrails, evaluation, governance, observability, and long-term AI platform architecture.

Key Responsibilities

Collaborate with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered capabilities that improve how associates work and how 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.
Use a combination of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and other related tooling.
Develop state-of-the-art foundation model optimization techniques to improve production performance, including scalability, cost, latency, and throughput.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
Define and guide technical AI architecture, integrating applied research advancements into production environments that meet reliability and scale requirements.
Help establish AI performance, safety, and transparency standards that guide model development and deployment across the company.
Drive multi-year platform initiatives that unify data, compute, and model lifecycle management under a cohesive enterprise AI architecture.
Mentor senior technical leaders across research, data, and engineering groups to develop Capital One’s next generation of AI technical leadership.

Required Qualifications

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in a related field 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.

Technology Focus

Programming: Python, Go, Scala, CUDA, Java
AI platforms and tooling: AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Deployment ecosystem: Open Source, SaaS

Preferred Qualifications

Experience architecting AI platforms with tradeoff decisions across cost, latency, throughput, and accuracy.
9 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
Proven 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 applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience building agentic AI systems and agentic workflows.
Demonstrated communication and presentation skills, including the ability to explain complex AI concepts to peers.
Recognition as an industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership.
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 in collaboration 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 based on requirements such as context length, token inputs, and token outputs.

Location and Salary

Location: McLean, VA (onsite)

Salary: USD 314,800 - 359,300 per year

Additional Employment Information

Capital One may sponsor a new qualified applicant for employment authorization for this position.
Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives may be discretionary or non-discretionary depending on the plan.
Applications are expected to be accepted for a minimum of 5 business days.
No agencies please.
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.

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Today

AI Engineer 3

Capital One San Jose, CA

San Jose, CA

Today

$177k - $201k/yr Full time Agents Ai Engineer Artificial Intelligence

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Job Description

The AI Engineer 3 role on Capital One’s Intelligent Foundations and Experiences (IFX) team focuses on building responsible, scalable AI capabilities spanning foundation model training, LLM inference, agent workflows, evaluation, governance, and observability, with an emphasis on optimizing performance, safety, and cost efficiency.

Key Responsibilities

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how 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.
Apply a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and related tools.
Develop and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for production AI systems.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, including measurable performance and safety metrics.
Build scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models across multiple environments.
Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies.
Support governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets.
Mentor junior AI engineers and promote engineering excellence, reproducibility, and responsible experimentation.

Required Qualifications

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 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 1 year of experience developing AI and ML algorithms or technologies.
At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java.

Technologies and Tools

AWS Ultraclusters
Huggingface
VectorDBs
PyTorch
Python, Go, Scala, CUDA, Java
Google Cloud, Azure
C++, C#, Golang
AWS
Retrieval-augmented generation (RAG)

Preferred Qualifications

Experience contributing to components of AI systems with tradeoff decisions across cost, latency, throughput, and accuracy.
4 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience developing, delivering, and supporting AI services.
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 building agentic AI systems and agentic workflows.
Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics such as accuracy, coherence, latency, and cost.
Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows.
Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems.

Compensation and Location

Location: San Jose, CA (onsite)
Salary Range: USD 176,500 - 201,400 per year

Benefits

Comprehensive, competitive, and inclusive health, financial, and other benefits to support total well-being.
Performance-based incentive compensation eligibility, which may include cash bonus(es) and/or long term incentives (LTI).

Team Overview

The Intelligent Foundations and Experiences (IFX) team brings Capital One’s vision for AI to life. The team works with partners across the company to advance the state of the art in science and AI engineering, and builds and deploys proprietary solutions central to the business, delivering value to millions of customers. The AI models and platforms empower teams across Capital One to enhance products with responsible and scalable AI in ways that drive high-leverage impact.

Ideal Candidate Profile

Enjoys building systems, takes pride in work quality, and focuses on doing the right thing.
Stays current with the latest research and can interpret scientific publications to apply novel techniques in production.
Can bring clarity to complex, undefined problems, dig into root causes, and communicate findings concisely.
Shares new ideas even when approaches are not yet proven.
Is deeply technical with strong foundations in engineering and mathematics, and can identify optimization opportunities across hardware, software, and AI.
Is resilient and capable of forging new paths to achieve business goals when the route is unknown.

Workplace and Process Notes

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 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 will consider for employment qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries.
If you need an accommodation, 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, email Careers@capitalone.com.
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.
Capital One Financial consists of multiple entities; roles posted in Canada, the United Kingdom, and the Philippines correspond to the respective Capital One entities described by the company.

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