AI Engineer 4 – AI Safety, Multimodal

Capital One

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

Posted 11/5/2026full-timeUnited StatesMid-LevelSenior💰 $197,300 - $245,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI systems, focusing on foundation model optimization, AI safety, and governance processes. Proficient in programming languages such as Python and Java, with a strong emphasis on scalable design and performance tuning.

Highest-signal resume keywords

AI System DevelopmentFoundation Model OptimizationPython ProgrammingAI Safety AlignmentCloud Platform Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI AlgorithmsMachine Learning TechnologiesModel TrainingModel InferenceDistributed Systems DesignPerformance TuningGovernance ProcessesScalable AI SolutionsMulti-Agent WorkflowsSimilarity Search

Soft Skills

MentoringCollaborationInfluencing Architectural Decisions

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchGPU UtilizationTPU Utilization

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in AI or Related Fields

Industry Keywords

AI GovernanceData GovernanceCompliance StandardsEthical AlignmentModel Performance Drift

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsJavaOpen SourcePythonPyTorchScalaC++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 state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput
Contribute to the technical vision and long-term roadmap of foundational AI systems
Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment
Define and maintain SLOs for AI reliability, including latency, uptime, and model performance drift
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
Lead cross-functional technical reviews for AI system deployments, ensuring security, data governance, and compliance standards
Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation

Requirements

What you’ll need

Bachelor'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, or a Master's degree in those fields plus at least 2 years of experience
At least 4 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
6+ years of experience deploying scalable and responsible AI solutions on cloud platforms
Experience designing, developing, delivering, and supporting AI services
Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
Experience developing and applying state-of-the-art techniques for optimizing training and inference software
Experience in AI Safety and LLM safety alignment
Experience with safety and vulnerability assessment of multi-modal applications using image/video plus text modality
Experience building agentic AI systems and workflows
Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale
Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules
Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

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 who require them