Manager, AI Solutions

Rich's•Buffalo, NY

3d•Onsite

About The Position

This role is responsible for leading a team of AI, data science, and analytics professionals in designing, developing, and implementing AI-powered solutions that support business objectives and deliver measurable enterprise value. This includes overseeing the development and deployment of predictive analytics, machine learning, generative AI, intelligent applications, and other emerging AI capabilities, while ensuring solutions are scalable, secure, governed, and aligned to enterprise technology standards. The role is also responsible for partnering with cross-functional business and technology teams to identify and prioritize opportunities for AI-driven innovation, translating business needs into practical solutions, and communicating complex technical concepts and business outcomes to stakeholders at all levels of the organization. This role is based at our WHQ in Buffalo, NY.

Requirements

Bachelor's Degree in Computer Science, Data Science, Statistics or related field.
5–7 years of experience in artificial intelligence, data science, analytics, software engineering, data engineering, or related technology disciplines.
Experience managing/leading technical teams and delivering data, AI, or technology solutions into production.
Strong knowledge of machine learning, statistical analysis, predictive analytics, generative AI, and emerging AI technologies.
Working knowledge of AI application patterns including retrieval-augmented generation (RAG), semantic search, intelligent automation, and AI agents.
Experience with programming languages such as Python and SQL; experience with modern software engineering practices is preferred.
Experience working with cloud-based data and AI platforms and technologies such as Azure, Databricks, Palantir or comparable platforms.
Knowledge of data platforms, data integration, APIs, databases, and modern data engineering practices.
Understanding of AI governance, data governance, security, privacy, responsible AI, and model lifecycle management.
Experience applying product-oriented and agile delivery practices to develop and continuously improve technology solutions.
Strong analytical and problem-solving skills, with the ability to translate complex business challenges into practical technology solutions.
Strong communication and stakeholder management skills, with the ability to explain technical concepts and business value to audiences at all levels of the organization.
Demonstrated ability to evaluate emerging technologies and determine their applicability, scalability, and value within an enterprise environment.

Nice To Haves

Masters Degree preferred.

Responsibilities

Lead and manage a team of AI, data science, analytics, and related technical professionals.
Develop and implement AI and data solution strategies that support business objectives and enterprise priorities.
Design, develop, and deploy predictive models, machine learning solutions, generative AI applications, intelligent agents, and other AI-powered capabilities to drive business insights, automation, and decision-making.
Lead the end-to-end delivery of AI solutions from opportunity identification and experimentation through production deployment, adoption, and continuous improvement.
Establish and promote reusable solution patterns, components, and capabilities to accelerate delivery and scale AI across the enterprise.
Ensure data quality, security, responsible AI, and governance requirements are incorporated into AI solutions and delivery practices.
Collaborate with cross-functional business and technology teams to identify, evaluate, and prioritize high-value AI opportunities.
Translate complex business problems into clearly defined AI solution strategies, requirements, and measurable outcomes.
Partner with data, technology, architecture, cybersecurity, and platform teams to ensure solutions are scalable, maintainable, and aligned with enterprise standards.
Monitor solution performance, adoption, cost, and business value to ensure AI investments deliver measurable outcomes.
Communicate complex AI, data, and technology concepts and recommendations effectively to technical and non-technical stakeholders.
Stay current with industry trends and emerging technologies in artificial intelligence, machine learning, generative AI, agentic AI, data, and automation.
Manage and allocate team resources to meet strategic priorities, delivery timelines, and business outcomes.