Principal AI Architect

Role Summary

We are looking for a senior technology leader with strong expertise across enterprise AI/ML, GenAI, distributed systems, cloud platforms, data infrastructure, and solution architecture. The role will work alongside the existing Ampleo core team across current and upcoming engagements.

The position is intended to complement existing technical leadership by providing additional architectural depth, client-facing technical leadership, portfolio-level governance, and delivery scalability. The ideal candidate should be hands-on, capable of translating business requirements into production-ready architecture, and comfortable operating across architecture, engineering, delivery, and senior stakeholder discussions.

Key Responsibilities

• Design and implement scalable cloud infrastructure for AI and data platforms.
• Work alongside with existing team to distribute technical leadership responsibilities across current and future engagements.
• Drive architecture decisions across application, data, AI/ML, integration, cloud, infrastructure, security, and observability.
• Guide the transition of AI/ML and GenAI prototypes into scalable, secure, production-ready enterprise platforms.
• Provide technical direction for LLM, RAG, AI agents, MLOps, model deployment, knowledge graph, vector database, and data platform solutions.
• Review solution designs for scalability, performance, security, reliability, maintainability, and cost efficiency.
• Participate in client discovery, architecture workshops, solution discussions, technical presentations, and senior stakeholder.
• Drive reuse of proven architecture, components, frameworks, patterns, and engineering practices across portfolio engagements.
• Identify technical risks, dependencies, architectural gaps, and delivery constraints and drive mitigation.
• Mentor senior engineers and technical leads and strengthen TAO's technical leadership capability.
• Help retain platform knowledge, architecture context, and engineering standards within TAO as the engagement portfolio expands.

Required Skills

• 10+ years of software engineering / technology experience with significant architecture and technical leadership exposure.
• 4+ years of experience in AI/ML, GenAI, data platforms, or related technologies.
• Strong enterprise-scale distributed systems and cloud architecture experience.
• Hands-on experience taking solutions from PoC / prototype through production deployment and operationalization.
• Strong AWS experience; exposure to Azure is an advantage.
• Strong programming background in Python, Java, Node.js, Rust, or similar.
• Strong understanding of LLMs, RAG, AI agents, MLOps, model deployment, and enterprise AI architecture.
• Experience with modern data, search, database, and vector technologies.
• Kubernetes, Docker, Terraform, and cloud-native engineering experience.
• Strong client-facing communication and stakeholder management skills.
• Experience leading distributed, cross-functional engineering teams.