Role overviewThe Cloud AI Platform Engineer builds and runs the cloud platforms that let mid-market clients put AI into production safely. You will design AI landing zones, deploy model and agent infrastructure, and harden vibe-coded and custom AI apps so they scale.
You'll join RSM's MCI (Managed Cloud & Infrastructure) Cloud practice, serving companies with $200M-$4B in revenue. You will work beside our Cloud Solutions Architects: together you will shape the solution; you build, automate, and operate it. Much of your work will be carried into RSM's Managed IT Services (MITS) as Managed AI and Managed Cloud, often as a Forward Deployed Engineer embedded with client IT teams.
Key responsibilitiesPlatform build- Design and deploy AI landing zones on Azure and AWS: networking, identity, policy, logging, and private endpoints.
- Stand up model platforms: Azure AI Foundry / Azure OpenAI, Amazon Bedrock, and SageMaker; integrate Anthropic, OpenAI, and open-weight models.
- Build infrastructure for RAG and agents: vector stores, orchestration, MCP servers, and API gateways.
- Codify everything in Terraform or Bicep, delivered through CI/CD pipelines.
Hardening and scaling- Take vibe-coded and prototype AI apps to production: containerize, add auth, secrets management, testing, and observability.
- Implement AI guardrails: content filtering, prompt-injection defenses, data loss prevention, and least privilege access.
- Align controls to client security baselines, Microsoft Purview, and frameworks such as NIST AI RMF and ISO 42001.
Operations and FinOps- Run LLMOps: model versioning, evaluation, monitoring, drift and quality alerts, and incident response.
- Instrument token and GPU consumption; build chargeback, quotas, and caching to control AI spend.
- Transition platforms into MITS run-state with runbooks, SLAs, and handoff to shared or dedicated teams.
Client advisory- Scope platform work, estimate effort, and contribute to SOWs and assessments.
- Explain trade-offs in plain language to CIOs, CISOs, and engineering leads.
- Contribute reusable accelerators, reference architectures, and the firm's vibe-coding harness.
Required qualifications- 5+ years in cloud, platform, or DevOps engineering; 1+ year deploying generative AI workloads in production.
- Hands-on depth in Azure or AWS, with working knowledge of the other.
- Infrastructure as code (Terraform or Bicep) and CI/CD (GitHub Actions or Azure DevOps).
- Containers and orchestration: Docker, Kubernetes (AKS or EKS), or serverless equivalents.
- Python plus one of TypeScript or Go.
- Cloud identity and security: Entra ID or IAM, Key Vault or Secrets Manager, private networking.
- Observability tooling such as Azure Monitor, CloudWatch, Datadog, or OpenTelemetry.
- Client-facing experience in consulting or a managed services provider.
- Ability to travel to client sites up to 25%.
Preferred qualifications- Bachelor's degree in a technical field or equivalent experience.
- Certifications: Azure AI Engineer Associate (AI-102), Azure Solutions Architect Expert, AWS Certified Machine Learning or GenAI Developer, HashiCorp Terraform Associate, FinOps Certified Practitioner.
- AI gateway and LLMOps tools: Azure API Management AI gateway, LiteLLM, LangSmith, Langfuse, or MLflow.
- Agent frameworks and protocols: Semantic Kernel, LangGraph, Bedrock Agents, MCP.
- Microsoft 365 Copilot, Copilot Studio, and Purview data governance.
- GPU capacity planning and cost management.
- Experience with mid-market clients and PE-backed portfolio companies.
At RSM, we offer a competitive benefits and compensation package for all our people. Learn more about our total rewards at https://rsmus.com/careers/working-at-rsm/benefits.
We believe flexibility and in-person connection both play an important role in how we work and grow. Most roles at RSM follow a hybrid workstyle, which means team members are aligned to an RSM office and come together in person when it best supports clients, teams, development or relationship-building. Some roles may be virtual or primarily on-site based on role requirements, team priorities and client needs.
At RSM, an employee's pay at any point in their career is intended to reflect their experiences, performance, and skills for their current role. The salary range (or starting rate for interns and associates) for this role represents numerous factors considered in the hiring decisions including, but not limited to, education, skills, work experience, certifications, location, etc. As such, pay for the successful candidate(s) could fall anywhere within the stated range.
Compensation Range: $134,000 - $269,000
Individuals selected for this role will be eligible for a discretionary bonus based on firm and individual performance.
