Director - AI/ML Solutions & Architecture

The Director of AI/ML Solutions & Architecture will provide strategic and technical leadership to shape, build, and scale enterprise AI capabilities. This role requires a visionary leader who can bridge business objectives with advanced AI/ML technologies, guide architecture decisions, and drive innovation across multiple programs and teams. The Director will play a key role in defining the AI roadmap, nurturing talent, and ensuring delivery excellence across AI initiatives.

Strategic Leadership

Define and drive the AI/ML strategy aligned with organizational goals and business outcomes.

Evangelize the adoption of Generative AI, LLMs, Deep Learning, and emerging AI technologies across business units.

Partner with executive leadership, product teams, and customers to identify high-impact AI opportunities.

Build and lead a multi-disciplinary AI team spanning architecture, data science, MLOps, and engineering.

Architectural & Technical Excellence

Oversee design and implementation of scalable AI systems leveraging LLMs/SLMs, RAG, Graph RAG, and vector databases. (AI Software Engineering)

Set architecture standards, governance frameworks, and best practices for AI model deployment and lifecycle management.

Guide the development of cloud-native, distributed AI solutions on platforms such as AWS, Azure, or GCP.

Ensure solutions are secure, cost-effective, and production-ready with strong observability and performance benchmarks.

Operational Excellence & Delivery

Lead the end-to-end delivery of complex AI/ML initiatives from ideation to deployment and continuous optimization.

Collaborate with product, engineering, and data teams to translate AI research into practical, scalable solutions.

Establish metrics and success criteria for AI project outcomes, driving measurable value for clients and business units.

Oversee code quality, documentation, and compliance across all AI/ML projects.

People Leadership

Mentor and upskill AI architects, data scientists, and engineers to build deep expertise across teams.

Foster a culture of innovation, experimentation, and continuous learning.

Represent the AI/ML practice in executive forums, industry events, and strategic customer engagements.

12+ years in AI/ML, Data Science, or Applied Research, with at least 45 years in leadership or architecture roles.

Proven experience leading enterprise-scale AI initiatives involving Generative AI, LLMs, or Deep Learning systems.

Strong expertise in Python, TensorFlow, PyTorch, and MLOps pipelines; familiarity with LangChain and vector databases is a plus.

Hands-on understanding of data engineering, cloud platforms, and distributed systems.

Demonstrated ability to translate business needs into scalable AI architectures and tangible outcomes.

Excellent communication, stakeholder management, and team leadership skills.