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Webster Bank

Managing Director, AI Engineer

Webster Bank, Stamford, CT, United States


If you’re looking for a meaningful career, you’ll find it here at Webster. Founded in 1935, our focus has always been to put people first--doing whatever we can to help individuals, families, businesses and our colleagues achieve their financial goals. As a leading commercial bank, we remain passionate about serving our clients and supporting our communities. Integrity, Collaboration, Accountability, Agility, Respect, Excellence are Webster’s values, these set us apart as a bank and as an employer.

Come join our team where you can expand your career potential, benefit from our robust development opportunities, and enjoy meaningful work!

AI/ML Engineer Responsibilities:

  • Envision, design, develop and assist with operationalizing end-to-end machine learning (ML) and AI pipeline.
  • As part of the development team, assist with the build of a robust application framework 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.
  • 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.
  • 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.
  • Develop and implement machine learning algorithms to enhance AI capabilities.
  • Collaborate with data scientists and engineers to optimize AI models and improve performance.
  • Design and integrate natural language processing systems for AI-powered applications.
  • Research and implement cutting-edge AI technologies and frameworks.
  • Create and maintain documentation for AI model development and deployment processes.
  • Test and validate AI models to ensure accuracy and reliability in real-world scenarios.

Experience Needed:

  • Required: Bachelor’s degree in computer science, Information Technology, or engineering.
  • Preferred: A master’s degree.
  • Required: 8+ years of experience in application design, development and implementation, with a strong background in banking services.
  • 4+ years working with AI/ML-driven solutions for financial services.
  • 5+ years’ experience in programming languages such as Python, Java, and/or C++.
  • 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).
  • Familiarity with Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
  • Hands on experience with Infrastructure as Code.
  • Experience working with AWS Bedrock, Sagemaker or other similar platforms.
  • Preferred: Certification in AI/GenAI, ML, Cloud Infrastructure, or related technologies.
  • Experience in a banking/financial services environment is essential.
  • Strong understanding of neural networks, computer vision, natural language processing, and/or reinforcement learning.
  • Knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud.
  • Experience in working with large datasets and data preprocessing techniques.
  • Familiarity with agile development methodologies and version control systems.
  • Strong problem-solving and analytical skills with a focus on continuous improvement.
  • Excellent communication and collaboration skills to work effectively in a multidisciplinary team environment.
  • Explaining the usefulness of the Gen AI models to a wide range of individuals within the organization, including collaborators and product managers.
  • Automating important infrastructure for the data science team.
  • Transforming the machine learning models into APIs to interact with other applications.
  • 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. Ability to work with offshore teams and guide the members as needed.
  • 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.

The estimated salary range for this position is $200,000.00 to $225,000.00. Actual salary may vary up or down depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position is eligible for incentive compensation.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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