AI Architect

AI Architect I (Manager)

Crowe

We are looking for a senior AI architect to lead end‑to‑end AI solution design and governance across our enterprise.

As part of the AI Transformation team, the AI Architect I (Manager) designs scalable, secure, and high‑performance AI systems that enable our clients to transform their business models using generative AI, machine learning, and software engineering.

• 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 ensure alignment 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 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 planning, and infrastructure‑as‑code (e.g., Terraform).
• Experience designing resilient, observable, multi‑region cloud architectures, and event‑driven data pipelines.
• Expertise in generative AI and LLM‑enabled systems, including RAG architectures, vector databases (e.g., Pinecone, Weaviate, FAISS), and model‑serving frameworks (e.g., vLLM, TGI).
• Experience designing prompt orchestration, guardrails, fine‑tuning workflows (e.g., LoRA/QLoRA), and secure LLM integration.
• Ability to participate in onsite or virtual design sessions; hybrid or remote work arrangements per organizational policy.
• Availability to support critical launches, reviews, or incident response as needed.

03/31/2026

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