AI Architect

Crowe•Tallahassee, FL

2d•Remote

About The Position

At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That’s why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry. Job Description: About Crowe AI Transformation Everything we do is about making the future of human work more purposeful. We do this by leveraging state-of-the-art technologies, modern architecture, and industry experts to create AI-powered solutions that transform the way our clients do business. The new AI Transformation team will build on Crowe’s established AI foundation, furthering the capabilities of our Applied AI / Machine Learning team. By combining Generative AI, Machine Learning and Software Engineering, this team empowers Crowe clients to transform their business models through AI, irrespective of their current AI adoption stage. As a member of AI Transformation, you will help distinguish Crowe in the market and drive the firm’s technology and innovation strategy. The future is powered by AI, come build it with us. About the Team We invest in expertise. You’ll have the time, space, and support to go deep in your projects and build lasting technical and strategic mastery. You’ll work with developers, product stakeholders, and project managers as a trusted leader and domain expert. We believe in continuous growth. Our team is committed to professional development and knowledge-sharing. We protect balance. Our distributed team culture is grounded in trust and flexibility. We offer unlimited PTO, a flexible remote work policy, and a supportive environment that prioritizes sustainable, long-term performance. About the Role 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. This role partners closely with engineering, data, cloud infrastructure, security, and product teams to define technical standards, integration patterns, and frameworks that operationalize predictive and generative AI capabilities. As a manager-level architect, the role leads solution design, mentors’ technical staff, facilitates architecture reviews, and ensures responsible AI, security, and governance standards are consistently applied to support a future-ready AI ecosystem.

Requirements

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.

Nice To Haves

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.
We expect the candidate to uphold Crowe’s values of Care, Trust, Courage, and Stewardship. These values define who we are. We expect all of our people to act ethically and with integrity at all times.

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.