23 hours ago
Boston, MA, USA +35 moreStaff+
Base Salary
$102k - $204k/yr
Responsibilities
- Architect and develop end-to-end generative AI, agentic, RAG, and AI-enabled enterprise workflow solutions.
- Lead solution architecture, technical feasibility, proof-of-concept delivery, and production deployment for client engagements.
- Remain hands-on with coding, prototyping, data integration, debugging, and technical implementation.
- Design cloud-native solutions across Azure, AWS, and GCP, including LLM, vector database, API, microservice, and enterprise integrations.
- Own solution design, engineering quality, risk management, scalability, security, reliability, performance, cost, and production readiness.
- Define evaluation, monitoring, observability, guardrail, and performance-optimization approaches for AI systems.
- Collaborate with AI engineering, data engineering, MLOps, DevOps, cloud infrastructure, and security teams.
- Mentor engineers through architecture reviews, code reviews, technical guidance, and hands-on problem-solving.
- Assess emerging AI frameworks, cloud capabilities, managed services, and engineering tools for innovation opportunities.
- Support client discovery, solution scoping, sales discussions, and communication of technical tradeoffs.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- At least 6 years of experience in production software engineering, cloud engineering, AI/ML engineering, or a related technical discipline.
- Strong hands-on software engineering experience with modern programming languages and production-grade application development and deployment.
- 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, RAG, embeddings, vector search, and agentic workflows.
- Ability to evaluate architectural tradeoffs involving scalability, security, performance, reliability, and cost.
- Understanding of software and AI application lifecycle management, including testing, evaluation, deployment, monitoring, and operational support.
- Strong client-facing communication skills and the ability to translate business requirements into technical solutions and mentor engineering teams.
- Demonstrated ownership of technical delivery, engineering quality, and risk management while remaining engaged in hands-on engineering.
- Preferred qualifications include a technical master’s degree or cloud/architecture certifications.
- Preferred experience includes production AI applications using OpenAI, Anthropic, Google, or similar providers; LLM and agent evaluation frameworks; Kubernetes; Terraform; observability; Azure AI; Amazon SageMaker; Google Vertex AI; Pinecone; Weaviate; FAISS; Microsoft Power Platform; Cursor; Replit; Retool; and n8n.
Benefits
- Flexible remote work policy and hybrid work arrangement.
- Unlimited paid time off.
- Supportive distributed-team culture focused on professional development, knowledge-sharing, and sustainable performance.
- Career coaching and growth opportunities in an inclusive culture.
- Travel may be required up to 80% depending on client and engagement requirements.
Categories
Forward Deployed
About Crowe LLP
Crowe LLP is a public accounting and consulting partnership based in Chicago that provides audit, tax, advisory, and technology-enabled consulting to companies, nonprofits, and public-sector clients. It operates as part of the Crowe Global network, which includes 300+ independent firms across 150+ countries. Founded in 1942, Crowe serves U.S. and international clients across regulated industries such as financial services, healthcare, manufacturing, and the public sector.