Senior Manager - AI Engineering

Vertex Inc.•Remote - PA, PA

About The Position

Lead AI engineering teams to design, build, and deploy AI-powered products that align with strategic business objectives and deliver measurable commercial value. Develop and execute AI engineering strategies and product roadmaps, balancing near-term delivery with long-term capability growth. Oversee end-to-end solution delivery — from concept through production — ensuring rigorous testing, validation, and QA for scalable, reliable AI systems. Partner cross-functionally with Product, Architecture, and Operations teams to integrate AI capabilities into existing systems; translate technical concepts into plain language for non-technical stakeholders. Champion AI adoption across the organization, driving a culture of innovation and agile best practices while expanding an AI-first mindset enterprise-wide. Engage senior leadership to shape AI use cases, articulate the capabilities and limitations of AI solutions, and ensure delivered products meet customer needs and compliance standards.

Requirements

10+ years of software engineering experience.
4+ years managing and growing engineering teams.
Proven track record of leading teams through multiple release cycles.
Demonstrated hands-on experience designing, implementing, and launching AI-powered products in production.
Clear examples of taking AI/ML initiatives from concept to commercially deployed solution.
Deep understanding of where AI creates business value and where it doesn't.
Ability to apply AI to the right problems, set realistic expectations, and guide teams toward the most effective solution for each challenge.
Strong engineering and system design skills.
Proficiency in one or more major programming languages.
Ability to guide teams on coding best practices and scalable architecture.
Excellent communication and stakeholder management skills.
Able to translate complex AI concepts into clear business terms.
Build consensus across diverse teams and leadership levels.
Proven ability to own AI engineering delivery.
Managing timelines, resources, and risks.
Maintaining iterative, transparent execution in line with agile methodology.

Nice To Haves

Bachelor's degree in Computer Science, Engineering, or a related technical field.
Master's or Ph.D. in Artificial Intelligence, Machine Learning, or Data Science preferred.
Hands-on familiarity with LLM concepts and techniques, including prompt engineering, temperature tuning, and model behavior management.
Experience with RAG (Retrieval-Augmented Generation) architectures and agentic AI workflows.
Familiarity with Azure AI Foundry and orchestration frameworks such as LangGraph and Semantic Kernel.
Experience with cloud-native MLOps, CI/CD pipelines, and containerization (Docker/Kubernetes) in Azure environments.
Equivalent combination of education, training, and relevant professional experience accepted in lieu of a formal degree.

Responsibilities

Design, build, and deploy AI-powered products.
Develop and execute AI engineering strategies and product roadmaps.
Oversee end-to-end solution delivery from concept through production.
Ensure rigorous testing, validation, and QA for scalable, reliable AI systems.
Partner cross-functionally with Product, Architecture, and Operations teams.
Translate technical concepts into plain language for non-technical stakeholders.
Champion AI adoption across the organization.
Engage senior leadership to shape AI use cases.
Articulate the capabilities and limitations of AI solutions.
Ensure delivered products meet customer needs and compliance standards.