JOB DESCRIPTION

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 Architect partners with cross functional teams in bridging the gap between complex AI technologies and practical business applications. Also, design the technical blueprints for AI systems, collaborate with technical and business teams to tailor AI-driven solutions, and oversee the implementation process to ensure that these solutions deliver tangible benefits. The AI Architect will provide the necessary leadership, analysis and design tasks related to the development of the application.

• 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.

Experience Needed

• Required: Bachelor’s degree in computer science, Information Technology, or engineering.
• Required: 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
• Preferred: A master’s degree or relevant certifications (e.g., BIAN, BPMN, PMP, TOGAF).
• Preferred: Certification in AI, ML, Cloud Infrastructure or related technologies
• 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.

The estimated salary range for this position is $170,000.00 to $195,000.00. 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.

LI-Hybrid

LI-FO1

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.
Stamford, CT
Posted: 6/23/2025
Job Reference #: R25_000000002

• 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