AI Architect

AI Architect (Manager)

Join Crowe as an AI Architect and help build the future of human work by turning advanced AI technology into transformative business solutions.

We create AI‑powered solutions that transform how our clients do business. By combining generative AI, machine learning, and software engineering, our new AI Transformation team extends Crowe’s established AI foundation and empowers clients at any stage of AI adoption.

• We invest in expertise so you can dive deep into projects and build lasting technical and strategic mastery.
• We believe in continuous growth and share knowledge across the team.
• We protect work‑life balance with unlimited PTO, a flexible remote policy, and a supportive environment that prioritises long‑term performance.

The AI Architect I (Manager) designs, governs, and evolves end‑to‑end architectural solutions that enable scalable, secure, and high‑performance AI systems across the enterprise. The role partners closely with engineering, data, cloud infrastructure, security, and product teams to define technical standards, integration patterns, and frameworks that ope rationalise predictive and generative AI capabilities. As a manager‑level architect, you will lead solution design, mentor technical staff, facilitate architecture reviews, and ensure responsible AI, security, and governance standards are consistently applied to support a future‑ready AI ecosystem.

• Architect end‑to‑end AI solutions, including model training pipelines, inference platforms, retrieval‑augmented generation (RAG) systems, and cloud ML platforms.
• Lead cross‑functional architecture and design reviews to align with enterprise architecture standards and business objectives.
• Collaborate with AI engineering, MLOps, Dev Ops, data engineering, and security teams to define scalable, secure, and reusable technical patterns.
• Design model‑serving and inference architectures optimized for latency, throughput, reliability, scalability, and cost efficiency.
• Define integration patterns for large language models (LLMs), vector databases, APIs, microservices, and event‑driven workflows.
• Establish and document architectural standards, reference architecture, diagrams, and decision records for enterprise adoption.
• Provide guidance on cloud architecture, Kubernetes‑based ML platforms, GPU capacity planning, and AI infrastructure modernization.
• Embed responsible AI, data governance, compliance, and security requirements into solution designs and architecture artifacts.
• Partner with security teams to assess technical risk and mitigate AI‑specific vulnerabilities.
• Mentor senior engineers and contribute to technical skill development across teams.
• Evaluate emerging AI platforms, frameworks, and cloud capabilities to inform long‑term architectural strategy.
• Participate in AI‑related incident reviews and drive improvements to system resilience and reliability.
• Drive standardization across AI development, deployment, and lifecycle management practices.

• 7+ years of experience in software engineering, AI/ML engineering, data engineering, or cloud architecture.
• Proven experience designing distributed systems and cloud‑native architecture.
• Strong understanding of the ML model lifecycle, AI infrastructure, and scalable system design.
• Expertise in API design, integration patterns, microservices, and event‑driven architectures.
• Ability to lead architectural decision‑making and align technical solutions with business needs.
• Excellent communication, documentation, and diagramming skills.
• Demonstrated ability to guide teams through complex technical design challenges.
• Willingness to travel occasionally for cross‑functional planning and collaboration.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
• Master’s degree, cloud architect certification, or enterprise architecture certification (e.g., TOGAF).
• Prior experience in technical leadership, architecture governance, or standards development.
• Advanced experience architecting ML platforms on AWS, Azure, or GCP, including Kubernetes‑based infrastructure, GPU…