Forward-Deployed AI Architect - Hands-On Leader

Crowe; The Woodlands (TX); Hybrid; USD 102,000 - 204,000; Full time

Job summary

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to design, deliver, and leadership in production AI solutions for client engagements. You will own solution architecture, mentor engineers, and stay hands-on across coding and prototyping.

You will lead cloud-native AI architectures on Azure, AWS, or GCP, work with LLMs, vector stores, and modern data platforms, and travel up to 80% to partner with clients. This role blends leadership with hands-on engineering.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• Minimum of 6 years of experience in production software engineering, cloud engineering, AI/ML engineering, or a related technical discipline.
• Strong hands-on software engineering experience, including proficiency in modern programming languages, application development, and production-grade solutions.
• 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.
• Strong communication and client-facing skills, with demonstrated ability to translate business requirements into technical solutions, explain complex architectural decisions, and mentor engineering teams.
• Demonstrated ownership of technical delivery, engineering quality, and risk management in collaborative, fast-paced environments, with a commitment to remaining actively engaged in hands-on engineering.
• Ability to travel up to 80%, depending on client and engagement requirements.

Responsibilities

• Architect and develop end-to-end AI solutions, including generative AI apps and agentic systems.
• 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, 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 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

Software engineering

Cloud architecture

AI/ML engineering

Generative AI

LLM patterns

Client facing

Leadership mentoring

Travel up to 80%

Education

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

Master's degree in technical field (preferred)

Tools

Kubernetes

Terraform

Power Platform

SageMaker

Vertex AI

Pinecone

Weaviate

FAISS

Job description

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to design, deliver, and leadership in production AI solutions for client engagements. You will own solution architecture, mentor engineers, and stay hands-on across coding and prototyping.

You will lead cloud-native AI architectures on Azure, AWS, or GCP, work with LLMs, vector stores, and modern data platforms, and travel up to 80% to partner with clients. This role blends leadership with hands-on engineering.