Enterprise AI Solutions Architect
New
S
StevensEnterprise AI Consulting
Work remotely from anywhere in the United States., Standard U.S. business hoursContractSenior
SalaryThis position is structured as an hourly contract role. Architects are paid an agreed hourly rate for time worked.
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Job Details
- Experience
- 7+ years
- Required Skills
- AWSMLOpsGenerative AI
Requirements
- 7+ years of relevant experience across software architecture, solutions architecture, application development, engineering, or technical consulting.
- Significant experience designing and delivering enterprise applications, platforms, or distributed systems.
- Hands-on experience architecting and implementing generative AI applications.
- Strong understanding of modern AI application patterns including RAG, agents, tool use, embeddings, vector search, model orchestration, and evaluation.
- Strong AWS architecture experience, including practical experience with Amazon Bedrock and SageMaker.
- Experience working with commercial AI platforms and models including OpenAI and Anthropic Claude.
- Strong understanding of modern application architecture, backend services, APIs, databases, and enterprise integration patterns.
- Familiarity with cloud engineering, DevOps, MLOps, CI/CD, and infrastructure as code.
- Experience leading technical discovery, architecture workshops, and customer-facing solution design.
- Strong written and verbal communication skills with the ability to explain complex technical concepts.
- Availability during standard U.S. business hours for customer workshops and meetings.
Responsibilities
- Lead technical discovery and architecture sessions with enterprise customers.
- Translate business problems and AI opportunities into practical solution architectures and implementation plans.
- Design enterprise AI applications using LLMs, RAG, agents, tool use, and modern cloud services.
- Design applications that integrate AI capabilities into existing enterprise systems and business workflows.
- Architect solutions primarily within AWS, including Amazon Bedrock and SageMaker.
- Evaluate models, platforms, frameworks, and architectural approaches for specific use cases.
- Define architecture across application services, APIs, data, model infrastructure, and observability.
- Account for enterprise requirements including security, privacy, governance, scalability, and cost.
- Review technical approaches and help engineering teams navigate architectural tradeoffs.
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