AI Engineer, Level 3

Capital One

. Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products .

Posted 9/29/2026full-timeUnited StatesMid-LevelSenior💰 $161,800 - $201,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing AI and ML algorithms, with a strong focus on scalable solutions and performance metrics. Proficient in collaborating across teams to enhance model evaluation and governance while mentoring junior engineers in best practices.

Highest-signal resume keywords

AI And ML Algorithm DevelopmentPython ProgrammingCloud Platform DeploymentFoundation Model OptimizationAgentic AI Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Algorithm DevelopmentML Algorithm DevelopmentPython ProgrammingGo ProgrammingScala ProgrammingCUDA ProgrammingJava ProgrammingC++ ProgrammingC# ProgrammingGolang Programming

Soft Skills

MentoringCollaborationAdvocacy For Engineering Excellence

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchGoogle CloudAzure

Certifications & Qualifications

Bachelor's Degree In Computer ScienceMaster's Degree In Computer Science

Industry Keywords

AI-Powered ProductsFoundation Model TrainingLLM InferenceModel EvaluationGovernanceObservabilityRetrieval-Augmented GenerationPrompt EngineeringSafety GuardrailsRed-Teaming Methodologies

Tech Stack

Tools & technologies

AWSAzureCloudJavaPythonPyTorchScalaC++Go

About the role

Key responsibilities & impact

Partner with 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, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
Invent and introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput of production AI systems
Contribute to the technical vision and long-term roadmap of foundational AI systems
Lead development and benchmarking of multi-turn conversational and tool-using agent workflows with measurable performance and safety metrics
Implement scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models
Collaborate with research and data engineering teams to curate datasets and improve model evaluation methodologies
Contribute to governance and security efforts for model traceability, lineage documentation, and version control
Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation

Requirements

What you’ll need

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 those 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
Experience contributing to AI system components with tradeoff decisions around 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 using Python, C++, C#, Java, CUDA, or Golang
Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost
Experience building agentic AI systems and workflows
Ability to evaluate and optimize LLM performance using quantitative metrics
Hands-on experience with retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows
Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies
Capital One will consider sponsoring a new qualified applicant for employment authorization

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Reasonable accommodations for applicants with disabilities
Drug-free workplace