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Crowe · 2 hours ago

AI Architect

Nashville, NY

Full-time

Hybrid

Senior Level

$102K/yr - $204K/yr

7+ years exp

Crowe is a leading public accounting, consulting, and technology firm in the United States, dedicated to innovation and client success. They are seeking an AI Architect to design and govern architectural solutions for scalable AI systems, collaborating with various teams to operationalize AI capabilities and ensure compliance with security and governance standards.

AccountingAdviceConsultingFinanceFinancial ServicesInformation TechnologyProfessional ServicesTax Consulting

No H1B

Responsibilities

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, DevOps, 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

Qualification

AI architectureCloud architectureMachine learningAPI designMicroservicesEvent-driven architectureKubernetesData engineeringCloud platformsCommunication skillsTechnical leadershipDocumentation skillsMentoring

Required

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

Preferred

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 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