AI Engineering Intern

Capital One

PhD AI engineering intern building agentic applications, multimodal systems, and scalable AI infrastructure. Contributing to customer-facing banking experiences serving Capital One customers.

Posted 9/8/2026full-timeNew York City • California, New York, Virginia • 🇺🇸 United StatesEntry Level💰 $176,000 - $192,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing AI systems, including multimodal search and intelligent document processing, while leveraging cloud platforms like AWS. Proficient in programming languages such as Python and Java, with a strong foundation in AI/ML algorithms and frameworks.

Highest-signal resume keywords

PhD In Computer Science, AI, Electrical Engineering, Or Related FieldAI/ML Algorithm DevelopmentPython ProgrammingAWS DeploymentAgentic Frameworks Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI System PrototypingMachine Learning AlgorithmsReinforcement LearningInference OptimizationMultimodal SearchNLPComputer VisionDistributed GPU FrameworksFine-Tuning PipelinesPre-Training Pipelines

Tools & Technologies

AWS UltraclustersPyTorchLangChainLangGraphLlamaIndexAutogenMCP/A2AFrontier-Labs Agent SDKs

Industry Keywords

AI-Native ProductsAgentic WorkflowsCloud PlatformsAI InfrastructureCustomer-Facing GenAI Workflows

Tech Stack

Tools & technologies

AWSAzureCloudGoJavaPythonPyTorchScala

About the role

Key responsibilities & impact

Partner with research scientists, product managers, and engineers to prototype and ship AI-native products
Research, prototype, and productionalize high-impact AI systems, including multimodal search, intelligent document processing, and autonomous agentic workflows
Design and optimize AI infrastructure, including fine-tuning and pre-training pipelines, reinforcement learning, inference optimization, guardrails, and evaluation frameworks
Use AWS Ultraclusters, PyTorch, and agentic frameworks to build AI systems
Architect agentic workflows that navigate tools, orchestrate multi-step reasoning, and integrate with complex microservice environments
Build Agentic AI applications and platform capabilities for customer-facing GenAI workflows, AI infrastructure, and internal agentic coding tools
Contribute to AI systems and AI-native experiences serving Capital One’s 100mm+ customers

Requirements

What you’ll need

Currently has, or is in the process of obtaining, a PhD in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with the degree expected by August 2029 or earlier
Must continue in the same course of study of the most recent degree after the internship
At least 1 year of experience or academic work developing AI and ML algorithms or technologies
At least 1 year of experience or academic work programming with Python, Go, Scala, or Java
Must be located in the continental United States
In-person attendance at the assigned location required for the internship duration
Experience or academic work deploying AI/ML systems on cloud platforms such as AWS, Google Cloud, or Azure
Experience or academic work developing and applying state-of-the-art techniques for optimizing AI/ML training or inference pipelines, including distributed GPU computational frameworks
Experience or academic work with AI/ML domains and systems such as LLM inference, search and retrieval, NLP, computer vision, guardrails, or memory
Familiarity with agentic frameworks such as LangChain, LangGraph, LlamaIndex, Autogen, MCP/A2A, or frontier-labs agent SDKs

Benefits

Comp & perks

Paid twelve-week internship from June through August
Comprehensive, competitive health, financial, and other benefits supporting total well-being
Potential evaluation for a full-time position after the internship
Employer immigration sponsorship may be available for a potential full-time AI Engineering role after internship completion
Top-tier developer tools including Claude Code and Windsurf