Platform Engineer (Python)

Job Title: Senior LLMOps / AI Platform Engineer
Location: Atlanta, GA
Visa: USC

Key Requirement: Azure OpenAI, Kubernetes, ArgoCD, Jenkins, Azure AI Search, Langfuse, LLMOps, RAG, CI/CD, Observability, Python Must be willing to work onsite in Atlanta, GA

Job Description: This role owns the operational foundation for George and other generative AI applications. The person should make the AI platform reliable, observable, cost-aware, secure, and release-ready across development, QA, and production environments.

Role Area Expected Ownership

Azure AI / Azure OpenAI Model deployments, quotas, TPM/RPM planning, rate-limit troubleshooting, deployment configuration, model upgrade support, fallback planning, and cost/performance monitoring.

Azure AI Search / RAG Infrastructure Index, indexer, skillset, embedding, semantic search, hybrid search, retrieval quality support, and performance troubleshooting for George knowledge sources.

CI/CD and Release Engineering Jenkins pipelines, build promotion, environment readiness, automated gates, release checklists, rollback planning, and deployment validation.

Kubernetes / Argo CD Argo CD sync health, manifest drift, Kubernetes pod health, environment promotion, scaling, config maps, secrets, and rollback operations.

Langfuse / Observability Trace ingestion, dashboards, prompt/version visibility, datasets support, experiment troubleshooting, latency, token usage, cost, and failure analysis.

Production Support Incident triage, root-cause analysis, operational runbooks, cross-team issue resolution, and executive-ready status reporting.

George-Specific Responsibilities

• Azure resource configuration
• Model operations
• RAG platform support
• Langfuse ownership
• Jenkins pipeline ownership
• Argo CD / Kubernetes ownership
• Operational observability
• Incident management

Responsibilities for Broader Agentic Applications Capability

• Agent runtime operations
• Tool-call observability
• Prompt/model release operations
• Evaluation gates in CI/CD
• Security and governance

Candidate Requirements Must-Have

• Azure cloud experience
• Kubernetes experience
• Jenkins or comparable CI/CD experience
• Argo CD / GitOps experience
• Observability and incident response
• LLM application understanding
• Python/scripting ability
• Cross-functional communication

Strongly Preferred

• Langfuse
• Azure AI Foundry / Azure OpenAI
• Azure AI Search
• Dynatrace / App Insights / OpenTelemetry
• LangGraph / MCP / agent frameworks
• IaC: Bicep, Terraform, Helm, Kustomize

Expected Deliverables

• LLMOps runbook
• Environment readiness checklist
• Release readiness gate
• Observability dashboard set
• Incident RCA template
• Model/prompt deployment process

30 / 60 / 90 Day Expectations

• First 30 days: Understand George architecture, Azure resources, model deployments, Jenkins, Argo CD, Langfuse, environments, release process, and current operational gaps. Produce an initial LLMOps assessment.
• First 60 days: Improve dashboards, runbooks, release checklists, Langfuse health checks, Azure quota monitoring, and Argo CD/Jenkins troubleshooting documentation.
• First 90 days: Implement or formalize AI release gates, improve observability coverage, reduce production troubleshooting time, and establish repeatable deployment/rollback process for model, prompt, index, and backend changes.

Cleo Consulting is an equal opportunity employer (Minorities/Women/Veterans/Disabled)

For applications and inquiries, contact: [email protected]