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Crowe

Public accounting, tax, and advisory services

Forward Deployed AI Architect

AI Application EngineeringPosted on Nov 11
Full-time$102.4k - $204.1k /yr

About the Job

Requirements

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

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.
  • Own 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, 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.

Desired Qualifications

  • A master's degree in a technical field or relevant cloud or architecture certifications is preferred.
  • Experience developing and deploying production AI applications using LLMs or agent frameworks from OpenAI, Anthropic, Google, or similar providers is preferred, including tool orchestration and multi-step agentic workflows.
  • Experience designing evaluation frameworks for LLM and agentic systems is preferred, including quality, reliability, safety, performance, and responsible AI considerations.
  • Advanced cloud and AI infrastructure experience is preferred, including Kubernetes, Terraform, observability, and managed AI services such as Azure AI, Amazon SageMaker, or Google Vertex AI.
  • Experience architecting RAG solutions, integrating vector databases such as Pinecone, Weaviate, or FAISS, and optimizing model inference or AI application performance is preferred.
  • Familiarity with AI-assisted development and low-code automation platforms such as Microsoft Power Platform, Cursor, Replit, Retool, or n8n is preferred, along with experience supporting client discovery, technical scoping, or proof-of-value engagements.

About the Company

Crowe

Public accounting, tax, and advisory services

Crowe provides audit, tax, and consulting services to public and private entities as a public accounting and advisory firm. It uses its industry knowledge to examine financial statements, plan and file taxes, and advise on business strategy and risk, delivering services through a global network. Crowe’s work is supported by its independent Crowe Global network, which brings together more than 200 member firms in over 130 countries to serve clients worldwide. This global scale enables access to industry specialists and diverse resources while maintaining a focus on client-specific needs. The company aims to help organizations manage financial reporting, regulatory compliance, and business decisions with accuracy and insight.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Chicago, IL
Founded
1942

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