Senior AI Platform Architect — Remote

MFS Investments; Cambridge (MA); Hybrid; USD 315,000 - 359,000; Full time

Job summary

Capital One is seeking a Sr. Staff AI Engineer (Remote Eligible) to partner with cross‑functional teams and deliver AI‑powered products that transform how associates work and how customers interact with Capital One.

You will design, train, deploy, and support AI software components, optimize foundation model performance, and lead architecture initiatives with a focus on safety, governance, and scale. A decade of AI/ML experience and cloud platform proficiency are required; Cambridge, MA is the

Qualifications

• Basic qualifications include a PhD or Master’s with 8–10+ years in AI/ML and programming.
• Experience building and deploying AI systems at scale with Python, C++, Java, or CUDA.
• Strong cloud experience across AWS, Google Cloud, or Azure and platform leadership.
• Ability to mentor teams and influence stakeholders up to SVP level.
• Proven track record in AI safety, governance, and long-term infrastructure planning.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, train, deploy, and support foundation models and agent workflows.
• Optimize performance, latency, and cost of large-scale AI systems.
• Lead architecture initiatives and establish AI safety and governance standards.

Skills

Python

Go

Scala

CUDA

Java

C++

C#

Golang

Education

Bachelor's Degree in Computer Science or related field

Master's Degree in Computer Science or related field

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Google Cloud

Azure

Job description

Capital One is seeking a Sr. Staff AI Engineer (Remote Eligible) to partner with cross‑functional teams and deliver AI‑powered products that transform how associates work and how customers interact with Capital One.

You will design, train, deploy, and support AI software components, optimize foundation model performance, and lead architecture initiatives with a focus on safety, governance, and scale. A decade of AI/ML experience and cloud platform proficiency are required; Cambridge, MA is the