AVP Cognitive Engineering (Generative AI)

Job description

Job Summary:
The Assistant Vice President (AVP) of Cognitive Engineering is a senior leader within the Enterprise Data and Information Management (EDIM) organization, responsible for shaping and executing strategy for data science, advanced analytics, and applied artificial intelligence (AI).

This key role leads the AI Center for Enablement, driving innovation, operational excellence, and the development of scalable AI capabilities.

AVP plays a pivotal role in fostering a culture of AI-as-a-service, enabling business units to harness AI technologies effectively and realize measurable value from AI investments.

In collaboration with business stakeholders, technology partners, and cross-functional teams, the AVP oversees the design and implementation of an enterprise AI platform, ensuring alignment with strategic goals and governance standards.

This leader brings deep expertise in cognitive technologies—such as Machine Learning, Natural Language Processing, Generative AI and Agentic AI—and is responsible for identifying emerging trends, guiding technology adoption, and transitioning AI solutions from incubation to enterprise-wide deployment.

The AVP serves as a catalyst for innovation, talent development, and cross-functional collaboration across the organization.


Responsibilities:

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Define and lead the strategic vision for Cognitive AI, Generative AI, Agentic AI, and Machine Learning capabilities, ensuring alignment with enterprise goals and transformation initiatives.

Provide executive oversight for the AI Center for Enablement, ensuring its services, platforms, and talent strategy drive enterprise-wide AI adoption, innovation, and measurable business value.

Oversee the development and enterprise-scale implementation of AI platforms, including the AI Foundational Platform, in collaboration with Enterprise Architecture, Cloud Engineering, and external technology partners.

Partners with senior leaders across business and IT to identify high-impact AI use cases, shape technology roadmaps, and accelerate the transition of AI solutions from incubation to production.

Champion the establishment of governance frameworks that ensure the ethical, secure, and explainable use of AI technologies, working closely with Model Risk Management, Cybersecurity, and the AI Working Group.

Lead the evaluation and infusion of emerging technologies in Cognitive Sciences, LLMs, NLP, Generative AI and Agentic AI through structured research, prototyping, and enterprise roadmap development.

Build and maintain strategic partnerships with leading AI vendors, cloud providers, and consulting firms to accelerate capability development and deliver tangible outcomes for members and internal stakeholders.

 Accelerate use of AI capabilities and toolset across the enterprise delivering productivity and driving process efficiencies for the workforce

Deliver the AI Literacy program across all organization levels in collaboration with industry partners and the Talent Development team.

Develop and scale high-performing AI Engineering and Operations teams, fostering a culture of continuous learning, technical excellence, and cross-functional collaboration.

Establish enterprise-level success metrics for AI initiatives, ensuring measurable impact, high adoption, and alignment with EDIM and enterprise architecture standards.

Enable federated AI development by supporting communities of practice and democratizing access to AI tools and services, driving process efficiencies and innovation across the organization.

Drive execution excellence by overseeing project planning, resource allocation, and budget management for AI initiatives.

Apply Scaled Agile principles to ensure timely delivery, iterative value realization, and alignment with enterprise priorities.


Qualifications and Education Requirements:

Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field- advanced degree preferred.

+ years of progressive experience in AI, Data Science and Advanced Analytics including leadership of enterprise-scale Generative and Agentic AI initiatives in complex, multi-functional environments.

Proven track record in designing, deploying, and scaling AI solutions—including LLMs, Agentic AI, and prompt engineering—within cloud-native, production-grade environments.

Deep expertise in AI platforms and technologies, including Azure OpenAI, Cognitive Services, and operationalizing AI infrastructure such as Model Garden and Control Plane.

Demonstrated ability to align AI strategy with enterprise transformation goals, delivering measurable business value through innovation, automation, and productivity acceleration.

Strong background in cloud architecture, system design, and building scalable, secure, and resilient AI platforms in service-oriented environments.

Experience in delivering AI augmented capabilities to generate productivity and process efficiencies (Github, CoPilot, IBM Watsonx, or similar)

Demonstrated ability to drive an AI Literacy program covering stakeholders at all levels in the organization by tailoring and evolving the curriculum relevantly.

Experience leading high-performing AI Engineering and Operations teams, fostering a culture of continuous learning, agile delivery, and technical excellence.

Extensive experience with AIOps practices including MLOps, building and managing end-to-end AI pipelines, implementing observability frameworks, monitoring model performance in production, managing incidents, and applying automated remediation techniques to ensure reliability, scalability, and compliance of AI systems.

Practical experience applying Scaled Agile Framework (SAFe) and Agile delivery principles to manage complex AI programs, budgets, and cross-functional execution.

Exceptional communication and executive presentation skills, with the ability to translate complex AI concepts into strategic insights for technical and non-technical stakeholders.


Desired Qualifications and Education Requirements:


Master's or in computer science, Data Science, Data Analytics, Statistics, Mathematics or related technical field.

Knowledge of instructions, standards, and procedures.

Expert knowledge of banking/financial industry trends, products, and services.

Expert knowledge of products, services, programs, policies and procedures.

Experience leading an AI Center for Enablement.

Experience building and supporting Enterprise grade APIs.

Required Skill Profession

Computer Occupations