AI Lead Architect

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Company Overview

A leading global professional services and technology organization is seeking an experienced AI Lead Architect to join its AI & Engineering practice. The organization partners with enterprise clients to transform technology platforms, modernize engineering capabilities, and accelerate innovation through artificial intelligence, cloud computing, and data-driven solutions. By leveraging cutting-edge engineering, AI, and cloud technologies, the company helps organizations improve business performance, modernize mission-critical operations, and deliver scalable digital transformation initiatives.

Key Responsibilities

• Architect and deliver enterprise AI platforms and applications using Google Cloud, Vertex AI, and Gemini.
• Design, fine-tune, evaluate, and govern Large Language Model (LLM) solutions, including prompt engineering, tool and function calling, safety policies, Vector Search, evaluation frameworks, deployment, inference optimization, and monitoring.
• Build Retrieval-Augmented Generation (RAG) and agentic AI solutions using Vertex AI Vector Search and BigQuery Vector capabilities.
• Design end-to-end AI architectures covering data pipelines, feature engineering, model lifecycle management, APIs, microservices, CI/CD, MLOps, and LLMOps using Vertex AI Pipelines and Cloud Build.
• Lead cloud-native application development utilizing GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL, Cloud Spanner, Memorystore, and Terraform.
• Establish and enforce application architecture standards and AI agent design patterns.
• Lead the design and development of enterprise-grade AI platforms that are scalable, secure, reliable, and optimized for production.
• Integrate and deploy Large Language Models and AI/ML solutions into enterprise environments while ensuring high performance and operational excellence.
• Collaborate with enterprise architects to align AI solutions with organizational technology strategies, governance frameworks, and architecture standards.
• Design and deploy cloud-native applications using modern hyperscaler technologies, including containers, Kubernetes, serverless services, and managed databases.
• Implement security controls and governance practices addressing AI-specific risks such as data privacy, model poisoning, adversarial attacks, and enterprise AI safety requirements.
• Mentor engineering teams and provide technical leadership throughout the AI solution lifecycle.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
• 8+ years of experience as a Software Architect or Solution Architect with expertise in designing and scaling enterprise applications.
• 5+ years of hands-on experience with Google Cloud, including at least two enterprise production implementations.
• 4+ years of experience designing and implementing Google Cloud networking, security controls, and landing zones using Terraform.
• 3+ years of experience building and operating containerized workloads on Google Kubernetes Engine (GKE), including autoscaling, ingress, monitoring, and observability.
• 3+ years implementing CI/CD and DevSecOps pipelines using Cloud Build, GitHub Actions, Jenkins, or similar tools.
• 3+ years leading cloud migration or modernization initiatives involving rehosting, replatforming, or refactoring workloads to Google Cloud.
• 2+ years applying AI and Generative AI technologies on Google Cloud using Vertex AI and Gemini, including production deployments involving RAG, Vector Search, prompt engineering, safety policies, and observability.
• Deep understanding of AI/ML concepts and experience implementing enterprise AI solutions using Large Language Models.

Preferred Qualifications

• Google Professional Machine Learning Engineer certification or an equivalent machine learning certification.
• Master’s degree in a technology-related field.
• 2+ years of experience leading high-performing engineering teams delivering enterprise AI platforms or applications.
• 1+ year of experience implementing LLMOps or MLOps using Vertex AI Pipelines, Cloud Build, or similar technologies.

Disclaimer

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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
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