Director AI Engineer

Description

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

The Intelligent Foundations and Experiences team sets the company's AI direction. It works with partners across the company on applied science and AI engineering, and builds and ships proprietary solutions central to the business that reach millions of customers. Its models and platforms let other teams add AI to their products in scalable, responsible ways.

Title: Director, AI Engineer.

Responsibilities

• Work with engineers, research scientists, technical program managers, and product managers to ship AI-powered products that change how associates work and how customers interact with the company.
• Lead design, development, testing, deployment, and support of AI software components such as foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Decide when to build and when to buy across open source and SaaS AI technologies, such as AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and others.
• Develop and introduce cutting-edge foundation model optimization methods that improve scalability, cost, latency, and throughput of large production AI systems.
• Shape the technical vision and long-term roadmap for the company's foundational AI systems.
• Recruit and retain top AI talent, support your team's personal and professional growth, and build a culture of learning that keeps pace with the state of the art in AI.
• Turn the enterprise AI strategy into portfolio-level plans across several product areas, balancing innovation with disciplined delivery.
• Spread strong AI engineering practices across teams through shared infrastructure, reusable components, and common observability and governance frameworks.
• Set the enterprise standard for Responsible AI, covering fairness metrics, model evaluation protocols, documentation requirements, and audit readiness.
• Work with research, compliance, and enterprise risk teams so deployed systems meet emerging ethical and regulatory standards.

Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 8 years of experience developing AI and ML algorithms or technologies; or a Master's degree in one of those fields plus at least 6 years of that experience.
• At least 3 years of people leadership experience.
• You enjoy building systems and take pride in the quality of your work. You care about doing the right thing and want to 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.
• You build others up, coach and mentor them, and stay hands-on when needed, leading by example.
• You adapt quickly, bring clarity to large, undefined problems, ask good questions, dig into root causes, and explain your findings concisely. You are willing to share new ideas before they are proven.
• You are deeply technical, with a strong base in engineering and mathematics. Your knowledge of hardware, software, and AI helps you find optimization opportunities others miss.
• You are a resilient pioneer who can find new paths to business goals when the route is unclear.
• Preferred: 5+ years of experience managing and leading an engineering team.
• Preferred: 7+ years of experience deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud.
• Preferred: Experience developing AI and ML algorithms or technologies, such as LLM inference, similarity search and vector databases, guardrails, or memory, using Python, C++, C, Java, CUDA, or Golang.
• Preferred: Experience building agentic AI systems and agentic workflows.
• Preferred: Passion for keeping up with the latest AI research and AI systems, and applying novel techniques in production with good judgment.
• Preferred: Strong communication and presentation skills, with the ability to explain complex AI concepts to peers.
• Preferred: Experience building and leading a multi-team AI organization that delivers several enterprise products or capabilities at once.
• Preferred: Proven ability to grow and carry out long-term AI platform strategies that match enterprise priorities and regulatory frameworks.
• Preferred: Experience setting up cross-functional operating rhythms and review cadences, such as OKRs, AI governance councils, and quarterly reviews.
• Preferred: Experience right-sizing models, instance counts, and hardware types against requirements such as context length and token inputs and outputs.

Conditions

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

Full-time annual base salary ranges by location: Cambridge, MA and McLean, VA: $269,100 - $307,200; New York, NY, San Francisco, CA, and San Jose, CA: $293,600 - $335,100. Pay for part-time roles is prorated to the agreed hours. Candidates hired elsewhere fall under that location's range, and the exact offer is stated in the offer letter.

Applications will be accepted for at least 5 business days.

Agencies are not accepted.

The company is an equal opportunity employer and does not discriminate, and it considers applicants with criminal histories in line with applicable law.

Benefits

• Eligible for performance-based incentive pay, which may include cash bonuses and/or long-term incentives (LTI), discretionary or non-discretionary depending on the plan.
• Health, financial, and other benefits. Eligibility depends on full- or part-time status, exempt or non-exempt status, and management level.