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Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible)

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 currently working on building a new AI native platform to empower our broader business community to execute AI assisted analysis across our many lines of business. We are building an AI native, at-scale (15,000+ users at destination), enterprise platform intertwining deterministic code with non-deterministic reasoning systems as well as both frontier and home grown AI models, to transform how our company works in the data analysis space.

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.

+ Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams

+ Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads

+ Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design

+ Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds

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

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:

+ Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 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 6 years of experience developing AI and ML algorithms or technologies

+ At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred Qualifications:

+ Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy

+ 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

+ Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems

+ Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP 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 developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

+ Experience in building agentic AI systems and agentic workflows

+ Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

+ Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

+ Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks

+ Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency

+ Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization

+ Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility

+ Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)

_Capital One will consider sponsoring a new qualified applicant for employment authorization for this position_

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

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