Distinguished AI Engineer at Capital One developing and optimizing AI infrastructure systems. Collaborating with cross-functional teams to enhance banking operations through responsible AI.
Responsibilities
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, 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, Nemo Guardrails, PyTorch, and more.
Invent and introduce state-of-the-art LLM 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.
Requirements
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, or Java
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 and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
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
2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen)
2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning)
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang.
Benefits
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Job title
Distinguished AI Engineer – Agentic AI Platform Infrastructure
Platform Engineer designing, building, and operating AI - enabled infrastructure for Comcast. Leading the implementation of cloud solutions ensuring scalability, reliability, and integration with applications and data teams.
Senior AI Platform Engineer designing and operating backend services for payroll platform automation. Involves integrating LLMs into production services and developing cloud infrastructure.
Lead and manage engineering teams delivering high - quality software solutions at Barclays. Fostering collaboration and technical excellence to align objectives with business goals.
Senior M365 & IAM Platform Engineer driving automation and identity engineering in a global automotive environment. Collaborating with cross - functional teams using M365, Entra ID, Azure Functions.
Full - stack Platform Engineer developing features for AI - powered product visibility. Collaborate on Auth, Billing, and Business Logic in a hybrid Buenos Aires role.
Platform Engineer strengthening cloud platform capabilities at Allica Bank. Involves deploying and automating cloud services across Microsoft Azure and Google Cloud Platform.
Platform Engineer with expertise in Databricks to manage and optimise the platform's performance and costs at Deloitte. Engaging in operational excellence and analysis of performance metrics.
Cloud Engineer at SDG Group managing data volume optimization for GCP. Designing workflows and ensuring efficient data processing in a hybrid work environment.
Product Reliability Engineer role at Kraken focused on scalable energy management solutions. Collaborating with teams to ensure product performance and system resilience in a hybrid work environment.
Frontend Platform Developer at Borrowell building foundational components for product teams in a remote - first environment. Collaborating with cross - functional teams to enhance code quality and app reliability.