Lead Engineer - AI

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 excited to offer a new opportunity to join our team as a Lead Engineer focused on Enterprise AI. We are looking for a visionary and hands-on AI lead with deep expertise in modern AI systems, LLM-based architectures, and software engineering. As a technical lead, you will shape the future of AI at TAG by engineering advanced AI applications across supervised, unsupervised, reinforcement, and generative learning paradigms, and delivering intelligent, scalable systems that power real-world healthcare applications.

Key Responsibilities:

• Develop and scale multi-agent systems leveraging LLMs, including Retrieval-Augmented Generation (RAG) and autonomous agent frameworks.

• Optimize agents for knowledge grounding, multi-step reasoning, and decision-making.

• Translate high-level designs into detailed solutions, including mock-ups, pseudo-code, and modular components.

• Lead the full AI/ML lifecycle: experimentation, evaluation, versioning, deployment, and continuous improvement.

• Design and implement distributed training pipelines, online inference systems, and low latency serving architectures optimized for real-world performance.

• Develop scalable, production-grade AI fabric using Vertex AI and modern cloud-native technologies.

• Implement intelligent observability and automation strategies to support AI system reliability and performance at scale.

• Focus on developing reusable AI components and orchestration layers that accelerate innovation across the enterprise.

Qualifications & Experience:

• PhD or Master’s degree in Computer Science, AI/ML, or related technical field.

• 8+ years of experience in AI/ML engineering, software engineering, or platform architecture.

• 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 experience with Vertex AI, including model training, orchestration, deployment, and monitoring.

• Proficiency in Python and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen).

• Expertise in distributed training, online inference, and low latency serving.

Preferred Qualifications:

• Experience with container orchestration (e.g., Kubernetes) and AI governance frameworks.

• Demonstrated contributions to open-source AI projects or publications in leading AI/ML venues.

• Experience with multi-modal models and advanced optimization techniques.

• Strong problem-solving and debugging skills in distributed environments.

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.

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