Full-Time

Director – AI Architecture

Confirmed live in the last 24 hours

Webster Bank

Webster Bank

Compensation Overview

$170k - $195kAnnually

+ Incentive Compensation

Senior, Expert

Stamford, CT, USA

Hybrid work arrangement; candidates will be required to work in-office some of the time.

Category
Applied Machine Learning
Deep Learning
AI Research
AI & Machine Learning
Required Skills
Kubernetes
Python
SAS
Data Science
Tensorflow
R
Neural Networks
Git
Machine Learning
Risk Management
Development Operations (DevOps)

You match the following Webster Bank's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Bachelor’s degree in computer science, Information Technology, or engineering
  • 5+ years of experience in automation design and implementation, with a strong background in banking operations
  • 3+ years working with AI/ML-driven solutions for financial services
  • Experience in a banking/financial services environment is essential
  • Knowledge of Data science and advanced analytics, including hands on experience of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks)
  • An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI
  • Familiarity with Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD
  • Exceptional problem-solving, analytical, and communication skills with the ability to engage and advise both non-technical and technical stakeholders
  • A proactive approach to leadership, with an emphasis on collaboration, empathy, customer centricity, and inclusiveness
  • Knowledge of enterprise architecture frameworks and methodologies (e.g., ArchiMate, TOGAF, Zachman)
  • Proficiency in evaluating and recommending emerging technologies and best practices
  • Excellent organizational, time management, and project management skills
  • Strong interpersonal and presentation skills; able to communicate complex concepts effectively
Responsibilities
  • Envision, design and assist with operationalizing end-to-end machine learning (ML) and AI pipeline
  • Assist with the build of a robust enterprise-wide architecture for AI and collaborate with data scientists, data engineers, developers, operations and security teams
  • Provide solutions and architecture for key business initiatives and own a portfolio of applications that span across consumer and commercial banking domains
  • Collaborate with data science and AI development teams to augment digital transformation efforts by identifying and piloting use cases
  • Understand and suggest ways to improve efficiencies in the workflow and pipeline architectures of ML and deep learning workloads
  • Discuss the feasibility of AI use cases along with architectural design with stakeholders and translate vision into realistic technical implementation
  • Work closely with security and risk teams to foresee and mitigate risks, such as training data poisoning, AI model drift etc, ensuring ethical AI implementation and improving trust in AI
  • Be change agents to help the organization adopt an AI-driven mindset
  • Stay abreast of upcoming regulations and ensure the enterprise is building solutions with appropriate guardrails to comply with ethical standards and industry regulations
  • Create reference architectures and identify reusable process, service components, and patterns to standardize and accelerate the bank’s AI adoption efforts
  • Create required architecture artifacts for the projects and ensure compliance with banks policies
  • Create a framework for evaluating and assessing AI opportunities and identifying the right set of technologies to use based on the relevant use cases
  • To ensure that AI platforms deliver on both business and technical requirements, seek to collaborate effectively with data scientists, data engineers, data analysts
  • Continuously evaluate new tools, technologies, and methodologies to advance innovation while ensuring scalability and security
  • Mentor junior staff members and provide guidance to cross-functional teams, fostering a culture of learning, innovation, and inclusivity
  • Work closely with the risk and compliance teams to assess the risks associated with solution implementations and develop appropriate mitigation strategies
Desired Qualifications
  • A master’s degree or relevant certifications (e.g., BIAN, BPMN, PMP, TOGAF)
  • Certification in AI, ML, Cloud Infrastructure or related technologies

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

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