The Aspen Group
Healthcare
StaffAIEngineer
Neural analysis suggests this role is
optimal for Staff candidates.
“Staff AI Engineer at The Aspen Group. Skills: AI Engineering, Agentic AI, LLM Architecture, Software Engineering. Architect enterprise-scale multi-agent systems. Develop enterprise-scale multi-agent systems”
Industry & Context.
Multi-step reasoning
What They're Looking For.
Must Have
BS in Computer Science or equivalent experience, 2+ years Agentic AI engineering, 4+ years AI/ML engineering, 8+ years software engineering or platform engineering, Proven track record building/deploying production AI/ML systems, Deep understanding modern AI model architectures, Hands-on expertise Vertex AI, Hands-on agent orchestration frameworks, Proficiency in Python, Proficiency LLM integration workflows, Proficiency MCP for tool integration, Proficiency A2A orchestration, Expertise distributed training, Expertise online inference, Expertise low latency serving architectures, Experience Kubernetes, Experience Cloud Run, Experience Dataflow/PubSub
Nice to Have
Experience AI governance frameworks, Experience responsible AI practices, Contributions to open-source AI projects, Publications in leading AI/ML conferences, Experience multi-modal models, Experience advanced optimization strategies, Experience automating MLOps infrastructure, Experience architecting MLOps infrastructure, Experience governing MLOps infrastructure
What You'll Do.
Architect enterprise-scale multi-agent systems
Develop enterprise-scale multi-agent systems
Leverage autonomous agent frameworks
Implement RAG pipelines
Optimize agents for orchestration
Optimize agents for knowledge grounding
Optimize agents for multi-step reasoning
Optimize agents for decision-making
Design distributed training workflows
Implement distributed training workflows
Design online inference systems
Implement online inference systems
Design low latency serving architectures
Implement low latency serving architectures
Engineer scalable AI fabric
Engineer secure AI fabric
Engineer compliant AI fabric
Engineer production-grade AI fabric
Engineer AI agent workflows
Create reusable agent orchestration layers
Create reusable observability hooks
Create reusable governance frameworks
Accelerate Agentic AI adoption
Partner with cross-functional stakeholders
Translate business requirements
Own full AI development lifecycle
Implement AI system reliability strategies
Implement AI system performance strategies
How You'll Work.
Team & Collaboration
Cross-functional stakeholders
Full Job Description
The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S. and has supported over 20,000 healthcare professionals and team members with close to 1,500 health and wellness offices across 48 states in four distinct categories: dental care, urgent care, medical aesthetics, and animal health. Working in partnership with independent practice owners and clinicians, the team is united by a single purpose: to prove that healthcare can be better and smarter for everyone. TAG provides a comprehensive suite of centralized business support services that power the impact of five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and Lovet. Each brand has access to a deep community of experts, tools and resources to grow their practices, and an unwavering commitment to delivering high-quality consumer healthcare experiences at scale. **Job Description:** As part of our continued investment in AI-driven innovation, we are looking for a **Staff AI Engineer** to join our growing AI team. This is a hands-on role delivering innovative solutions for the healthcare enterprise. The ideal candidate will bring deep expertise in modern AI systems, multi-agent systems & frameworks, LLM-based architecture, and software engineering. **Key Responsibilities:** * Architect and develop enterprise-scale multi-agent systems leveraging LLMs and autonomous agent frameworks using Google ADK, Agentspace, MCP, RAG, and A2A orchestration. * Design and implement RAG pipelines using BigQuery and Vertex AI Engine for knowledge grounding and factually accurate responses. * Optimize agents for orchestration, knowledge grounding, multi-step reasoning, and decision-making. * Design and implement distributed training workflows, online inference systems, and low latency serving architectures optimized for real-world performance, using Google cloud-native services. * Engineer scal
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