The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S., supporting over 23,000 healthcare professionals and team members at more than 1,150 locations across 48 states. Our five supported healthcare practices operate under the brands Aspen Dental, ClearChoice, WellNow, Chapter Aesthetic Studio, and Lovet. We’re committed to enabling healthcare professionals to focus on patient care while we handle the business operations that support them.
We are seeking a Senior Manager of AI Platform & Delivery.
Our Platform Engineering organization — spanning Delivery, Cloud, and SRE — is expanding its leadership bench as the company scales its adoption of AI. We’re hiring a Senior Manager, AI Platform & Delivery to lead the teams that build and operate the foundation every team uses to work with AI safely, reliably, and productively; built on Google Cloud and anchored by our two flagship enterprise AI platforms: Claude Enterprise and Google’s Gemini Enterprise Agent Platform (formerly Vertex AI).
In this role you’ll own two closely related charters:
AI Platform: the strategy, roadmap, operation, and governance of our enterprise AI platforms, the surrounding ecosystem of plugins, connectors, and marketplace extensions, and the agents, tooling, and paved paths that turn AI from a novelty into everyday infrastructure.
Delivery: leading the Delivery function that ships platform capabilities to the rest of engineering, ensuring teams get reliable, well-paved paths to build on.
You’ll lead a team that includes AI Platform Engineers and Delivery engineers (both mentoring and growing the team) while setting technical direction, owning operational excellence, and partnering across Security, IT, and the business. This is a hands-on leadership role: you’ll spend most of your time leading people and shaping strategy, while staying close enough to the technology to make sound architectural and operational calls.
This is a strong fit for an engineering leader who has built and run high-performing platform, DevOps, SRE, or MLOps teams, is energized by AI enablement, and wants to own an emerging AI platform end to end from provisioning and onboarding through operations, governance, and adoption at scale.
What you ll do
Team Leadership & People Management
Lead, coach, and grow a team of AI Platform and Delivery engineers through hiring, onboarding, performance management, and career development.
Set clear goals and priorities, foster a healthy, inclusive, high-trust team culture, and create the conditions for engineers to do their best work.
Balance hands-on technical involvement with delegation, empowering the team to own systems end to end.
AI Platform Operations Strategy & Roadmap
Own the vision, strategy, and roadmap for our enterprise AI platforms (Claude Enterprise and Gemini Enterprise) on Google Cloud, increasingly through the Gemini Enterprise Agent Platform (formerly Vertex AI).
Prioritize across competing demands (adoption, reliability, cost, security, and governance) and communicate trade-offs clearly to leadership and stakeholders.
Set direction for the surrounding ecosystem: plugins, connectors, MCP integrations, and the internal marketplace of approved extensions, agents, and integrations (Agent Garden, Model Garden).
Software Delivery Leadership
Own the software delivery platform and toolchain end to end. This includes source control and CI/CD (GitLab, GitLab CI), GitOps-based continuous delivery (ArgoCD), and deployment orchestration (Spinnaker), and set the standards teams build, release, and ship on.
Drive secure-by-default, standardized pipelines and GitOps workflows: least-privilege service accounts, keyless auth (Workload Identity Federation), reproducible deploys, and progressive delivery (canary, blue/green) with safe, fast rollbacks across GKE and Cloud Run.
Lead the Delivery function so platform capabilities and paved paths ship reliably and predictably to application and engineering teams; manage delivery tooling roadmap, upgrades, and migrations (e.g., consolidating or evolving CI/CD and continuous-delivery platforms).
Champion developer experience — golden paths, paved roads, reference architectures, self-service onboarding, and templates that make the right thing the easy thing.
Drive execution and delivery performance across the team’s workstreams: planning, prioritization, healthy delivery cadence, and steady improvement in DORA metrics (deployment frequency, lead time, change failure rate, MTTR).
Operational Excellence
Ensure our AI platforms and services are reliable, performant, observable, and cost-effective in production.
Mature how the team operates: on-call, incident response, post-incident reviews, SLAs, and operational metrics for both deterministic and non-deterministic (AI) systems.
Own platform cost governance (usage, seat utilization, and spend) across Claude Enterprise, Gemini Enterprise, and Google Cloud.
Governance, Security & Compliance
Partner with Security, IT, and leadership to define and enforce standards, guardrails, and policies for safe, secure, and responsible AI use including for plugins, extensions, and the marketplace.
Oversee identity, access, and provisioning at scale, focusing on things such as SSO, role and group management, access reviews, and the full user lifecycle across platforms.
Ensure evaluation harnesses and quality checks are in place to measure AI output quality and catch regressions.
Stakeholder & Cross-functional Partnership
Serve as the primary point of contact for AI platform and delivery topics across the business; translate technical capabilities into business value.
Communicate roadmap, adoption, and outcomes to leadership and partner teams.
Manage relationships with key vendors and partners (e.g., Anthropic and Google Cloud), including licensing, seats, and roadmap alignment.
Requirements
8 years in platform engineering, DevOps, SRE, MLOps, cloud, or a related software/infrastructure discipline, including 2–3 years directly managing or leading engineering teams.
Demonstrated success building, leading, and growing high-performing engineering teams — hiring, mentoring, and developing engineers.
Strong technical foundation: Google Cloud (GCP), containers and orchestration (Docker, Kubernetes), and infrastructure-as-code (Terraform or similar).
Strong grasp of modern CI/CD and continuous delivery — pipeline design (GitLab CI or equivalent), GitOps (ArgoCD or similar), and deployment orchestration / progressive delivery (Spinnaker or similar) — including secure, keyless authentication to cloud providers.
Experience operationalizing AI/LLM or data/ML workloads in production — or a strong infrastructure foundation and clear eagerness to lead in the AI space.
Working knowledge of how LLMs and AI APIs are used in applications (prompting, RAG, embeddings, tool/function calling, agents).
Track record of owning strategy and roadmap, setting priorities, and driving delivery across multiple workstreams.
Excellent written and verbal communication and stakeholder-management skills; able to influence leadership and explain technical concepts to non-experts.
Solid grasp of operational best practices, monitoring/observability, and cost governance.
Based in (or willing to relocate to) the Chicago area and able to work onsite/hybrid.
Nice to Have (Preferred)
Direct experience with Claude Enterprise; deployment, administration, onboarding, plugins, connectors, or MCP.
Experience with Gemini Enterprise and/or the Gemini Enterprise Agent Platform (formerly Vertex AI) — Agent Builder/Agent Engine, Agent Garden, Model Garden, RAG/Vector Search.
Experience leading AI enablement, governance, or practical AI programs across an organization.
Experience managing a plugin/extension ecosystem or an internal app/agent marketplace.
Background partnering with FinOps to drive cloud and AI cost visibility and accountability.
Experience building or scaling internal developer platforms or developer-experience functions.
Direct, hands-on experience operating GitOps and continuous delivery at scale — ArgoCD, Spinnaker, GitLab / GitLab CI, and Argo Rollouts or Flux — across Kubernetes (GKE) and serverless (Cloud Run).
Familiarity with DORA metrics and a track record of measurably improving software delivery performance.
Experience managing vendors and partner relationships with cloud and AI providers.
Familiarity with our stack: Google Cloud / BigQuery, Atlassian (Jira/Confluence), incident.io, Grafana/OTEL, Sentry, Microsoft 365.
Degree in Computer Science, Engineering, or a related field — or equivalent practical experience.
About the Team
You’ll join our Platform Engineering organization, which spans Delivery, Cloud, and SRE and reports to the Senior Director of Platform Engineering. We’re a pragmatic team focused on giving the rest of the company reliable, well-paved infrastructure to build on — and we’re now extending that mission to AI.
*This role is onsite 4 days/week in our Chicago office (Fulton Market District)
A generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match
Salary: $165,000-195,000/year plus 15% performance bonus