AI Engineer 4 (Gen AI Platform Services: Agentic AI)

Capital One; San Francisco (CA); In loco; USD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

Capital One is seeking an AI Engineer 4 to join the Gen AI Platform Services team, focusing on scalable, responsible AI systems and production-grade AI infrastructure in San Francisco. You will build and optimize AI components, including foundation models, inference, and multi-agent workflows, while collaborating across engineering, research, and product groups.

You will mentor junior engineers, drive integration with Open Source and SaaS AI tools, and contribute to the long-term roadmap for

Competenze

• Bachelor’s or Master’s in CS/AI/EE/CE or related fields with required AI/ML experience
• Proficient programming in Python/Go/Scala/CUDA/Java or similar
• Experience deploying scalable AI/ML solutions is preferred

Mansioni

• Partner with cross-functional teams to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components
• Leverage Open Source and SaaS AI tech (AWS Ultraclusters, Huggingface, VectorDBs, PyTorch)
• Invent foundation model optimization techniques to improve performance, cost, latency, and throughput
• Own end-to-end architecture for complex AI systems with maintainability and observability
• Define and maintain SLOs for AI reliability (latency, uptime, drift)
• Collaborate with infra to optimize GPU/TPU usage and model inference pipelines
• Lead cross-functional technical reviews for new AI deployments, ensuring security and governance
• Mentor senior engineers on scalable design and production translation

Formazione

Bachelor’s Degree in CS/AI/EE/CE or related fields + 4 years experience

Master’s Degree in CS/AI/EE/CE or related fields + 2 years experience

Strumenti

Python

Go

Scala

CUDA

Descrizione del lavoro

AI Engineer 4 (Gen AI Platform Services: Agentic AI)

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

What You’ll Do:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our 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, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
• Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment
• Define and maintain service-level objectives (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 new AI system deployments, ensuring security, data governance, and compliance standards are met
• Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss
• You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown

Basic Qualifications:

• 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 Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
• At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred Qualifications:

• 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 (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• 3+ years of experience with Kubernetes
• Experience designing, 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-