Hands-On AI Architect Manager - Client-Facing

Crowe; Knoxville (TN); Hybrid; USD 102,000 - 204,000; Full time

Benefits offered by this job

Unlimited PTO

Flexible remote work policy

Supportive environment for sustainable

Career growth opportunities

Job summary

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to design, develop, and deliver production-ready AI solutions for clients. You will own solution architecture, feasibility, and production readiness while remaining hands-on in coding and prototyping.

Join Crowe Studio's Forward Deployed Engineering practice to collaborate with clients and cross-functional teams, delivering scalable, secure AI applications across cloud platforms. Travel up to 80% may be required.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 6 years of experience in production software engineering, cloud engineering, AI/ML engineering, or related technical discipline.
• Strong hands-on software engineering experience, including proficiency in modern programming languages and the design and deployment of production-grade solutions.
• Demonstrated experience architecting cloud-native applications and distributed systems using Azure, AWS, or GCP, including APIs, microservices, enterprise integrations, and data workflows.
• Working knowledge of generative AI and LLM application patterns, including prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, and agentic workflows.
• Ability to assess technical feasibility, evaluate architectural tradeoffs, and make sound engineering decisions considering scalability, security, performance, reliability, and cost.
• Understanding of software and AI application lifecycle management, including testing, evaluation, production deployment, monitoring, and operational support.
• Ability to travel up to 80%, depending on client and engagement requirements.

Responsibilities

• Architect and develop end-to-end applied AI solutions, including generative AI applications, agentic systems, retrieval-augmented generation (RAG), and AI-enabled enterprise workflows.
• Lead solution architecture for AI build and proof-of-concept engagements, ensuring solutions are technically feasible, scalable, secure, and aligned with client business objectives.
• Remain hands-on across solution development, including application coding, data integration, prototyping, debugging, and technical implementation.
• Design and implement cloud-native AI solutions using Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), and relevant AI platforms and services.
• Define architecture and integration patterns for large language models (LLMs), vector databases, APIs, microservices, enterprise data platforms, and client systems.
• Take ownership of technical feasibility, solution design decisions, and build quality from initial discovery through production deployment.
• Guide solutions through Architecture Review Board processes, ensuring alignment with enterprise architecture standards, security requirements, responsible AI principles, and production readiness expectations.
• Assess technical feasibility during client discovery sessions, solution scoping, and sales support discussions, clearly communicating technical tradeoffs, risks, and recommended approaches.
• Establish engineering standards, reusable architectural patterns, technical documentation, and development best practices across client engagements.
• Design solutions with appropriate evaluation frameworks, monitoring, observability, guardrails, and performance optimization to support reliable AI operations.
• Collaborate with AI engineering, data engineering, MLOps, DevOps, cloud infrastructure, and security teams to deliver integrated enterprise solutions.
• Evaluate technical tradeoffs among custom development, managed AI services, and low-code or automation platforms to select appropriate implementation strategies.
• Identify and address technical risks, including performance, scalability, security, reliability, and cost considerations.
• Mentor engineers through architecture reviews, code reviews, technical guidance, and hands-on problem-solving to strengthen engineering quality and team capabilities.
• Evaluate emerging AI frameworks, cloud capabilities, and engineering tools to identify opportunities for innovation and continuous improvement.

Skills

Six years of experience in production/

Hands-on software engineering

Cloud architecture

LLM / AI patterns

Client communication

Software lifecycle management

Ownership of technical delivery

Travel availability

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Master's degree in a technical field

Tools

Kubernetes

Terraform

Observability tooling

Azure AI

AWS SageMaker

Google Vertex AI

Job description

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to design, develop, and deliver production-ready AI solutions for clients. You will own solution architecture, feasibility, and production readiness while remaining hands-on in coding and prototyping.

Join Crowe Studio's Forward Deployed Engineering practice to collaborate with clients and cross-functional teams, delivering scalable, secure AI applications across cloud platforms. Travel up to 80% may be required.