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

Description

The company is building responsible, reliable AI systems and has long used machine learning for real-time, personalized customer experiences, such as alerts about unusual charges and live answers to customer questions.

The Intelligent Foundations and Experiences (IFX) team leads the company's AI direction. It works with partners across the company to advance AI science and engineering and builds proprietary solutions that serve millions of customers, plus AI models and platforms that other teams use in scalable, responsible ways.

Responsibilities

• Work with engineers, research scientists, technical program managers, and product managers to ship AI products that change how associates work and how customers interact with the company.
• Design, build, test, deploy, and support AI software, covering foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Work with open source and SaaS AI tools, such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
• Develop and apply new foundation model optimization methods to improve scalability, cost, latency, and throughput of large production AI systems.
• Help shape the technical vision and long-term roadmap for the company's foundational AI systems.
• Own the end-to-end architecture of complex AI systems, keeping them maintainable, observable, and ethically aligned.
• Define and maintain SLOs for AI reliability, covering latency, uptime, and model performance drift.
• Work with infrastructure engineers to improve GPU/TPU utilization and speed up model inference pipelines.
• Lead cross-functional technical reviews of new AI deployments to confirm they meet security, data governance, and compliance standards.
• Mentor Principal and Senior Associates on scalable design, performance tuning, and turning research into production systems.

Requirements

• You enjoy building systems, take pride in your work, and care about doing the right thing. You want to solve problems that help change banking for good.
• You keep up with the latest research and can read scientific papers well enough to apply new techniques in production with judgment.
• You adapt quickly, bring clarity to large, undefined problems, and ask questions to find root causes. You explain findings clearly and concisely, and you are willing to propose new ideas even when they are unproven.
• You have a strong background in engineering and mathematics. Your knowledge of hardware, software, and AI helps you spot optimization opportunities others miss.
• You are resilient and can find new paths to business goals when the route is unclear.
• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 4 years of experience developing AI and ML algorithms or technologies; or a Master's degree in one of those fields plus at least 2 years of the same experience.
• At least 4 years of programming in Python, Go, Scala, CUDA, or Java.
• Preferred: Experience leading AI systems development with tradeoffs among cost, latency, throughput, and accuracy.
• Preferred: 6+ years deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud.
• Preferred: Experience designing, building, delivering, and supporting AI services.
• Preferred: Experience building AI and ML technologies such as LLM inference, similarity search and VectorDBs, guardrails, or memory, in Python, C++, C, Java, CUDA, or Golang.
• Preferred: Experience applying state-of-the-art methods to optimize training and inference software for hardware utilization, latency, throughput, and cost.
• Preferred: Experience building agentic AI systems and agentic workflows.
• Preferred: Keeps up with the latest AI research and systems and applies novel techniques in production with judgment.
• Preferred: Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• Preferred: Experience defining AI model governance processes, including producibility, lineage tracking, and automated retention schedules.
• Preferred: Proven ability to influence architecture decisions across several AI product lines or platforms.

Conditions

The company will consider sponsoring a new qualified applicant for employment authorization for this position.

Full-time annual salary ranges by location: Cambridge, MA and McLean, VA: $197,300 - $225,100; New York, NY, San Francisco, CA, and San Jose, CA: $215,200 - $245,600. Offers for other locations follow that location's range, and the exact amount appears in the offer letter. Part-time pay is prorated to the agreed hours.

The role may be eligible for performance-based incentive pay, which may include cash bonuses and/or long-term incentives (LTI), and may be discretionary or non-discretionary depending on the plan.

Applications will be accepted for at least 5 business days.

No agencies. The company is an equal opportunity employer and considers qualified applicants with criminal histories in line with applicable law.

Benefits

• Comprehensive health, financial, and other benefits. Eligibility depends on full- or part-time status, exempt or non-exempt status, and management level.