Track record of building and deploying production-grade AI/ML systems
Deep understanding of modern AI architectures like transformers
Strong expertise with Vertex AI and Google Agentic AI stack
Hands-on with agent orchestration frameworks such as Google ADK or LangChain
Proficiency in Python and AI integration workflows
Expertise in distributed training and low latency architectures
Responsibilities
Architect and develop multi-agent systems using LLMs and various orchestration frameworks
Design and implement RAG pipelines with BigQuery and Vertex AI Engine
Optimize agent systems for reasoning and decision-making
Design distributed training workflows and low latency serving architectures
Engineer production-grade AI workflows using Vertex AI
Create reusable orchestration layers and governance frameworks
Collaborate with stakeholders to translate business needs into technical specifications
Manage the complete AI development lifecycle from data collection to monitoring
Implement observability and automation for AI system performance
Benefits
Generous paid time off
Health, dental, and vision insurance
401(k) savings plan with match
Full Job Description
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 scalable, secure, compliant and production-grade AI fabric and AI agent workflows using Vertex AI and modern cloud-native technologies.
Create reusable agent orchestration layers, observability hooks, and governance frameworks that accelerate Agentic AI adoption across TAG brands.
Partner with cross-functional stakeholders in translating business requirements into technical specifications.
Own the full AI development lifecycle - from data collection and implementation to deployment and monitoring.
Implement intelligent observability and automation strategies to ensure AI system reliability and performance at scale.
Qualifications & Experience:
BS in Computer Science, or related technology field or equivalent experience.
2+ years of experience in Agentic AI engineering.
4+ years of experience in AI/ML engineering
8+ years of experience in software engineering, or platform engineering
Proven track record of building and deploying production-grade AI/ML systems at scale.
Deep understanding of modern AI model architectures (e.g., transformers, diffusion models) and system design.
Strong hands-on expertise with Vertex AI (including model training, pipelines, orchestration, deployment, and monitoring) and Google's Agentic AI stack.
Hands-on with one or more of these agent orchestration frameworks: Google ADK/Agentspace,LangChain, LangGraph, LlamaIndex, CrewAI or AutoGen.
Proficiency in Python, LLM integration workflows, MCP (Model Context Protocol) for tool integration and A2A (Agent-to-Agent) orchestration for multi-agent workflows.
Expertise in distributed training, online inference, and low latency serving architectures.
Experience with Kubernetes, Cloud Run, and Dataflow/PubSub for scalable deployment.
Preferred Qualifications:
Experience with AI governance frameworks and responsible AI practices (Vertex AI Model Monitoring, BigQuery logging, Looker dashboards).
Contributions to open-source AI projects or publications in leading AI/ML conferences.
Experience with multi-modal models and advanced optimization strategies & frameworks.
Experience automating, architecting and governing production grade MLOps infrastructure to scale, optimize, and observe AI workloads.
Annual Salary Range: $170,000-$200,000/year, with a generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match.
About Aspen Dental Management Inc
Aspen Dental Management Inc is a dental support organization that provides business services to independently owned and operated dental practices in the United States. The company's services include marketing, human resources, accounting, and information technology. Aspen Dental Management's affiliated practices offer a range of dental services, including general dentistry, orthodontics, and oral surgery. The company was founded in 1998 and is headquartered in East Syracuse, New York.
