Production AI Infra & MLOps Engineer

LaStellar Group; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

LaStellar Group is seeking a Platform Engineer to own and operate our production AI and data platform infrastructure across Azure and GCP. You will manage cloud infra, CI/CD pipelines, container orchestration, and agent operations to keep systems reliable, scalable, and production-grade.

You will build observability tooling, support data platform integration, and implement auto-scaling for container workloads. The role demands 3–5 years in DevOps/MLOps with strong curiosity about AI systems.

Qualifications

• 3–5 years in software engineering, DevOps, MLOps, or platform engineering with production ownership.
• Hands‑on Docker and container orchestration experience in Azure and/or GCP.
• Terraform across cloud providers — you've designed it, not just configured it.
• CI/CD pipeline experience with Git-based release management.
• Systems thinker — you troubleshoot end‑to‑end, not just at the surface.
• Genuine curiosity about AI and agentic systems — excited to grow into deeper platform concepts.
• Strong signals in policy-as-code, observability depth, and multi-cloud tooling are a plus.

Responsibilities

• Operate and scale live agentic AI systems across Azure and GCP, ensuring availability, performance, and resilience.
• Build and maintain observability tooling for agent execution—logging, tracing, alerting, and performance monitoring.
• Support integration of agents with data platforms and MCP servers.
• Implement auto-scaling strategies for containerized workloads across Azure Container Apps, Cloud Run, and GKE.
• Contribute to evaluation frameworks and quality standards for AI agents in production.
• Own Python-based services’ lifecycle—from containerization to deployment and runtime behavior.
• Build shared tooling and internal packages to accelerate data science workflows.
• Write and maintain Terraform across Azure and GCP for registries, identities, secrets, and networks.
• Develop CI/CD pipelines and release workflows across data science and engineering repos, enforcing security and runbooks.

Skills

Docker

Container orchestration

CI/CD pipelines

Infrastructure as code

End-to-end troubleshooting

AI/agented systems curiosity

Tools

Azure

GCP

Azure Container Apps

GKE

GCP Cloud Run

Vertex AI

Managed Identities

VNets

Key Vault

Secret Manager

OpenTelemetry

LangChain

MLflow

Prefect

dbt

Snowflake

Job description

LaStellar Group is seeking a Platform Engineer to own and operate our production AI and data platform infrastructure across Azure and GCP. You will manage cloud infra, CI/CD pipelines, container orchestration, and agent operations to keep systems reliable, scalable, and production-grade.

You will build observability tooling, support data platform integration, and implement auto-scaling for container workloads. The role demands 3–5 years in DevOps/MLOps with strong curiosity about AI systems.