AI Platform Engineer

TAG - The Aspen Group•Chicago, IL

10d•$111,000 - $135,000•Hybrid

About The Position

The Aspen Group (TAG) is seeking an AI Platform Engineer to join their expanding Platform Engineering organization. This role will lead and maintain the company’s AI platform across the business, focusing on Google Cloud and enterprise AI platforms like Claude Enterprise and Google’s Vertex AI (Gemini Enterprise Agent Platform). The engineer will be responsible for operating and extending these platforms, managing user onboarding, curating the ecosystem of plugins and connectors, and building agents and tooling to integrate AI into everyday infrastructure. This is a hands-on, high-impact position with significant growth potential as the AI practice matures, suitable for an engineer with experience in Platform Engineering, DevOps, SRE, or MLOps who is passionate about AI enablement and end-to-end platform ownership.

Requirements

3–5 years in platform engineering, DevOps, SRE, MLOps, backend, or a similar software/infrastructure role.
Strong programming skills in Python, plus comfort with at least one other language (JavaScript/TypeScript, Go, or Java a plus).
Hands-on experience with Google Cloud (GCP) as a primary cloud platform.
Working knowledge of how LLMs and AI APIs are used in applications (prompting, RAG, embeddings, tool/function calling, agents) — or strong fundamentals and clear eagerness to learn.
Experience with containers and orchestration (Docker, Kubernetes) and infrastructure-as-code (Terraform or similar).
Experience building and operating AI Delivery workstreams and production services.
Experience with identity, access, and provisioning — SSO/SAML/SCIM, role and group management, and user lifecycle (onboarding/deprovisioning).
Solid grasp of AI monitoring/observability and operational best practices.
Clear written and verbal communication; able to explain technical concepts to non-experts and write strong documentation.
Based in (or willing to relocate to) the Chicago area and able to work onsite/hybrid.

Nice To Haves

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 managing and creating platform extensions, a plugin ecosystem, or an internal app/agent marketplace.
Direct experience with LLMOps/MLOps tooling — model serving, vector databases, evaluation frameworks, agent orchestration (e.g., ADK, LangChain/LlamaIndex).
Experience deploying or integrating enterprise AI tools (e.g., Claude, Gemini, GitHub Copilot, NotebookLM) across an organization.
Experience building internal developer platforms or developer-experience tooling.
Familiarity with AI governance, security, or responsible-AI frameworks.
Experience running enablement, training, or developer-advocacy programs.
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.

Responsibilities

Deploy, scale, and operate Claude Enterprise, Gemini Enterprise, and related AI/LLM workloads in production, ensuring reliability, performance, and cost-effectiveness.
Build and maintain CI/CD pipelines, infrastructure-as-code, and deployment automation for AI applications, agents, and models.
Instrument AI systems with monitoring, logging, and observability, and respond to issues as part of an on-call rotation.
Manage integrations with model providers and APIs, including authentication, rate limits, quotas, and failover.
Own the end-to-end onboarding experience for Claude Enterprise and Gemini Enterprise, including provisioning, license assignment, SSO, and role configuration.
Manage the full user lifecycle, ensuring accurate and auditable access, entitlements, and seat assignments.
Build automation and self-service flows for user access to approved AI tools.
Track adoption and seat utilization, and partner with IT and Security on identity, access reviews, and provisioning workflows.
Manage and curate platform extensions across the AI stack, including plugins, connectors, and marketplace integrations.
Run the internal marketplace/catalog of approved extensions, agents, and integrations.
Define processes for requesting, evaluating, and governing extensions.
Build and integrate custom plugins and connectors to link AI platforms with internal systems and data.
Build internal tools, copilots, and agents to facilitate AI adoption in workflows.
Develop reusable templates, reference architectures, and libraries for common AI patterns.
Integrate AI capabilities into existing internal systems and the developer toolchain.
Help engineers and teams adopt approved AI tools through documentation, office hours, demos, and support.
Create and maintain best-practice guides, prompt libraries, and onboarding materials.
Gather user feedback to prioritize platform improvements.
Help define and implement standards, guardrails, and policies for safe, secure, and responsible AI use.
Build evaluation harnesses and quality checks to measure AI output quality.
Partner with Security, IT, and leadership on compliance, access provisioning, and cost governance.