AI Lead/Architect

About the Role:

We are seeking a visionary and hands-on AI Architect to lead a mission-critical new team responsible for bridging the gap between pioneering academic research and robust, enterprise-grade AI solutions.

This is not a purely academic or purely production role it's the dynamic center where they meet. You will be the technical force driving the transformation of brilliant prototypes into scalable, secure, and performant products that solve real-world problems for our clients.

If you thrive on solving complex, ambiguous technical challenges that require both deep AI expertise and modern software architecture leadership and are passionate about mentoring and guiding a high-calibre team, this is your opportunity to build the next generation of core capabilities for our clients.

Required Qualifications:

Technical Leadership

• Proven experience deploying AI/ML products to production across multiple domains.
• Deep understanding of LLMs, Prompt Models, and large-scale neural network architectures.
• Expertise in designing fusion prompt models and statistical models for diverse applications.
• Strong foundational experience in traditional machine learning algorithms and techniques.
• Proficiency in Python for both research and production code.
• Hands-on experience with AWS (EC2, S3, Lambda, DynamoDB, SageMaker, EKS/ECS, etc.) and strong knowledge of containerization (Docker/Kubernetes).
• Experience with system architecture design and microservices.
• Strong knowledge of database design (SQL and NoSQL).
• Familiarity with API design (RESTful or GraphQL).

Leadership & Process Acumen

• Minimum 2-3 years leading or mentoring technical teams of 3+ members.
• Demonstrated ability to convert concepts into practical product constraints and make tough build/buy/scope decisions.
• Expertise leading technical product life cycles from concept to delivery.
• Experience with agile development methodologies (Scrum/Kanban).
• Strong decision-making skills in ambiguous situations.

Preferred Qualifications

• Experience in end-to-end model building, deployment, and performance monitoring.
• Experience with real-time systems or streaming data.
• Experience with model compression, optimization techniques, or model serving frameworks.
• First-author publication in Q1 SCI journal or top-tier CS conference OR experience as a reviewer for academic engineering/CS journals.
• Open-source contributions or technical blog writing.