[Hiring] Staff AI Engineer @TAG - The Aspen Group

Role 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

• 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.

Requirements

• 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.

Benefits

• Annual Salary Range: $170,000-$200,000/year.
• Generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match.