{"id":2555825,"url":"https://alion.io/job/teamtag-ai-platform-engineer","title":"AI Platform Engineer","company":{"id":2231267,"name":"Teamtag","domain":"teamtag.com","url":"https://alion.io/company/teamtag-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":111000,"max":135000,"currency":"USD","period":"year","gross":null,"usd_annual":135000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Go","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false},{"name":"BigQuery","optional":true},{"name":"Confluence","optional":true},{"name":"Copilot","optional":true},{"name":"Google ADK","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Grafana","optional":true},{"name":"Jira","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Sentry","optional":true},{"name":"Vertex AI Agent Builder","optional":true}],"status":"live","first_seen_at":"2026-09-08T00:00:00Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-14T23:39:01Z","board_verified":true,"closed_at":null,"days_open":37,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":37},"description":"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.\nWe are seeking an AI Platform Engineer.\nOur Platform Engineering organization - spanning Delivery, Cloud, and SRE - is expanding to lead and maintain the company’s AI platform across the business. We’re hiring an AI Platform Engineer to own the foundation that lets every team use AI safely, reliably, and productively - built on Google Cloud and anchored by our two flagship enterprise AI platforms: Claude Enterprise and Google’s Vertex AI (Gemini Enterprise Agent Platform).\nIn this hands-on role you’ll:\nOperate and extend these platforms\nManage the end-to-end onboarding of users and teams onto them\nCurate and govern the surrounding ecosystem of plugins, connectors, and marketplace extensions\nBuild the agents, tooling, and paved paths that turn AI from a novelty into everyday infrastructure.\nYou’ll do this on Google Cloud, increasingly through the Gemini Enterprise Agent Platform (formerly Vertex AI). It’s a high-impact position with significant room to grow as our AI practice matures.\nThis is a strong fit for an engineer with a few years of Platform Engineering, DevOps, SRE, or MLOps experience who is excited about AI enablement; someone who likes owning a platform end to end, from provisioning and onboarding through operations and governance.\nResponsibilities\nAI Platform Operations & LLMOps (on Google Cloud)\nDeploy, scale, and operate Claude Enterprise, Gemini Enterprise, and related AI/LLM workloads in production (be it Google Cloud or Anthropic); keeping them reliable, performant, and cost-effective.\nBuild and maintain CI/CD pipelines, infrastructure-as-code, and deployment automation for AI applications, agents, and models, increasingly on the Gemini Enterprise Agent Platform (formerly Vertex AI).\nInstrumentation of AI systems with monitoring, logging, and observability (tracking latency, quality, usage, and spend) and responding to issues as part of an on-call rotation.\nManage integrations with model providers and APIs (Claude, Gemini, and code assistants), including authentication, rate limits, quotas, and failover.\nOnboarding & User Lifecycle Management\nOwn the end-to-end onboarding experience for Claude Enterprise and Gemini Enterprise: provisioning, license/seat assignment, SSO, and group/role configuration.\nManage the full user lifecycle - onboarding, role changes, and deprovisioning - keeping access, entitlements, and seat assignments accurate and auditable.\nBuild automation and self-service flows so new users and teams get access to approved AI tools, with the right permissions, from day one.\nTrack adoption and seat utilization, and partner with IT and Security on identity, access reviews, and provisioning workflows.\nPlatform Extensions & Marketplace\nManage and curate platform extensions across our AI stack - Claude Enterprise plugins, connectors, and MCP integrations, plus Gemini Enterprise / Agent Platform extensions (Agent Garden, Model Garden, connectors).\nRun the internal marketplace/catalog of approved extensions, agents, and integrations: review, vet, publish, version, and retire them.\nDefine how extensions are requested, evaluated, and governed - balancing easy self-service adoption against security and data-handling requirements.\nBuild and integrate custom plugins, connectors, and MCP servers that link our AI platforms to internal systems and data.\nInternal AI Tooling & Paved Paths\nBuild internal tools, copilots, and agents - on the Gemini Enterprise Agent Platform and Claude - that make it easy for teams to adopt AI in their workflows.\nDevelop reusable templates, reference architectures, and libraries for common patterns (RAG, summarization, agents, evaluations).\nIntegrate AI capabilities into existing internal systems and the developer toolchain.\nEnablement & Training\nHelp engineers and other teams adopt approved AI tools through clear documentation, office hours, demos, and hands-on support - tightly linked to onboarding.\nCreate and maintain best-practice guides, prompt libraries, and onboarding materials.\nGather feedback from users to prioritize platform improvements and surface new opportunities.\nGovernance & Best Practices\nHelp define and implement standards, guardrails, and policies for safe, secure, and responsible AI use (data handling, access control, acceptable use) - including for plugins, extensions, and the marketplace.\nBuild evaluation harnesses and quality checks to measure AI output quality and catch regressions.\nPartner with Security, IT, and leadership on compliance, access provisioning, and cost governance.\nRequirements\n3-5 years in platform engineering, DevOps, SRE, MLOps, backend, or a similar software/infrastructure role.\nStrong programming skills in Python, plus comfort with at least one other language (JavaScript/TypeScript, Go, or Java a plus).\nHands-on experience with Google Cloud (GCP) as a primary cloud platform - AWS or Azure experience is welcome, but GCP is central to this role.\nWorking 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.\nExperience with containers and orchestration (Docker, Kubernetes) and infrastructure-as-code (Terraform or similar).\nExperience building and operating AI Delivery workstreams and production services.\nExperience with identity, access, and provisioning - SSO/SAML/SCIM, role and group management, and user lifecycle (onboarding/deprovisioning).\nSolid grasp of AI monitoring/observability and operational best practices.\nClear written and verbal communication; able to explain technical concepts to non-experts and write strong documentation - important for onboarding and enablement.\nBased in (or willing to relocate to) the Chicago area and able to work onsite/hybrid.\nNice to Have (Preferred)\nDirect experience with Claude Enterprise - deployment, administration, onboarding, plugins, connectors, or MCP.\nExperience with Gemini Enterprise and/or the Gemini Enterprise Agent Platform (formerly Vertex AI) - Agent Builder/Agent Engine, Agent Garden, Model Garden, RAG/Vector Search.\nExperience managing and creating platform extensions, a plugin ecosystem, or an internal app/agent marketplace.\nDirect experience with LLMOps/MLOps tooling - model serving, vector databases, evaluation frameworks, agent orchestration (e.g., ADK, LangChain/LlamaIndex).\nExperience deploying or integrating enterprise AI tools (e.g., Claude, Gemini, GitHub Copilot, NotebookLM) across an organization.\nExperience building internal developer platforms or developer-experience tooling.\nFamiliarity with AI governance, security, or responsible-AI frameworks.\nExperience running enablement, training, or developer-advocacy programs.\nFamiliarity with our stack: Google Cloud / BigQuery, Atlassian (Jira/Confluence), incident.io, Grafana/OTEL, Sentry, Microsoft 365.\nDegree in Computer Science, Engineering, or a related field - or equivalent practical experience.\nAbout the Team\nYou’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.\n*This role is onsite 4 days/week in our Chicago office (Fulton Market District)\nA generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match\n$111,000-135,000/year","description_format":"text","description_chars":7991,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-14T19:10:24Z"}],"visa":[],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":1,"p_active":0.527,"p_room":0.45,"age_days":37,"expected_fill_days":19,"reasons":["conf:0","win:tail"],"computed_at":"2026-10-15T00:12:32Z"},"pay":{"stated_usd_annual":135000,"is_top_pay":false},"html_url":"https://alion.io/job/teamtag-ai-platform-engineer","json_url":"https://alion.io/job/teamtag-ai-platform-engineer.json","meta":{"generated_at":"2026-10-15T00:12:32Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":149,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":2231267},"rest":"https://alion.io/mcp/rest/get_company?id=2231267"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fteamtag-ai-platform-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fteamtag-ai-platform-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fteamtag-ai-platform-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/teamtag-ai-platform-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fteamtag-ai-platform-engineer"}]}