AI Technical Lead

Overview

Working closely with Business Integrators, data scientists, engineers, and client stakeholders, the AI Technical Lead leads the technical design and implementation of AI-driven solutions. The role combines deep technical expertise with leadership skills to guide teams in building high-quality AI systems that deliver real business value.

The AI Technical Lead also ensures that solutions are aligned with enterprise architecture standards, data governance principles, and responsible AI practices.

Key Responsibilities

Design AI Solution Architectures

• Translate business use cases into scalable AI and data architectures.


• Define the technical approach for AI solutions, including model architecture, data pipelines, and system integration.


• Design end-to-end AI systems, from data ingestion and model development to deployment and monitoring.


• Ensure solutions integrate seamlessly with the client’s existing IT and data ecosystem.

Lead Technical Implementation

• Provide technical leadership to multidisciplinary teams of AI engineers, data scientists, and developers.


• Guide teams through the full lifecycle of AI development, from prototyping to production deployment.


• Establish best practices for AI engineering, model development, and MLOps.


• Ensure code quality, system reliability, and performance.


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Collaborate with Business and Product Stakeholders

• Work closely with Business Integrators to translate business requirements into technical solutions.


• Support the evaluation of AI opportunities by assessing technical feasibility and implementation complexity.


• Communicate technical architecture and solution choices clearly to both technical and non-technical stakeholders.

Ensure Scalable and Responsible AI Solutions

• Implement best practices for security, privacy, and compliance in AI systems.


• Design AI solutions with responsible AI principles in mind, including transparency, fairness, and explainability.


• Ensure proper monitoring, retraining, and lifecycle management of AI models.

Contribute to Innovation and Technical Strategy

• Stay up to date with emerging AI technologies, frameworks, and best practices.


• Contribute to the development of reusable AI components, frameworks, and architectural standards.


• Support the evolution of the organization’s AI and data architecture strategy.

Required Profile

• Strong experience in AI, machine learning, or advanced data engineering roles.


• Proven experience designing and implementing production-grade AI systems.


• Deep understanding of AI/ML technologies, data platforms, and modern software architecture.


• Experience with cloud-based AI platforms and data ecosystems.


• Ability to lead technical teams and guide complex AI implementations.


• Strong communication skills and the ability to explain technical concepts clearly.

Key Competencies

• AI and machine learning architecture


• Data platform architecture


• MLOps and model lifecycle management


• System integration and scalability


• Technical leadership


• Cross-functional collaboration