Solution Architect

Sourced from drjobpro.com

Purple Drive seeks an AI Solution Architect in Bellevue, WA to lead the design and delivery of secure, scalable AI solutions spanning generative AI, agentic AI, machine learning, data, and cloud. The architect will take AI use cases from concept to production, designing governed AI agents with guardrails, human oversight, and observability. The role partners with business, engineering, and governance teams to define reference architectures, MLOps/LLMOps practices, and responsible AI controls.

• Define end-to-end AI solution architectures aligned with business outcomes and enterprise standards
• Design LLM application architectures including prompt orchestration, RAG, agents, vector databases, and model gateways
• Architect agentic AI solutions with agent loops, harnesses, tool orchestration, and human-in-the-loop controls
• Establish agent evaluation, tracing, and monitoring practices for production reliability
• Define MLOps and LLMOps practices covering versioning, testing, deployment, observability, and rollback
• Lead architecture reviews, discovery workshops, proof-of-concept initiatives, and production-readiness assessments
• Mentor technical teams and contribute to AI engineering standards and knowledge assets

• Bachelor's degree
• Experience designing and delivering AI/ML solutions including generative AI and LLM applications
• Strong knowledge of agentic AI patterns (ReAct, planner-executor), RAG, and vector search
• Hands-on familiarity with cloud AI platforms such as Azure AI Foundry, AWS Bedrock/SageMaker, or Google Vertex AI
• Proficiency in Python, containerization, Kubernetes, CI/CD, and infrastructure as code
• Experience with APIs, microservices, event-driven architecture, and data integration
• Knowledge of security, privacy, responsible AI, and regulatory compliance in solution design

• Consulting, presales, solution estimation, or customer-facing architecture experience
• Experience delivering AI solutions in regulated or large-scale enterprise environments
• Industry knowledge in telecommunications, customer operations, or network operations
• Experience establishing AI centers of excellence or enterprise AI governance frameworks