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AI Infrastructure / MLOps Engineer — NYC
Summary by AIEngineer.careers
AI Infrastructure / MLOps Engineer — NYC is a MLOps Engineer role (full-time). with LaStellar Group. in NEW YORK CITY METROPOLITAN AREA, US. Compensation shown: $180K–$225K. Imported listing (source: linkedin.com). Apply on the employer's site (linkedin.com).
Imported listing (source: linkedin.com) · Apply on linkedin.com
NEW YORK CITY METROPOLITAN AREA · US
$180K–$225K
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from linkedin.com
LaStellar Group is seeking an AI Infrastructure/MLOps Engineer to own the production systems behind its AI and data platforms. You'll operate and scale agentic AI systems across Azure and GCP, build CI/CD pipelines and Terraform-managed infrastructure, and drive observability and reliability. This on-site role in New York City is ideal for engineers with strong Python and cloud platform skills.
Responsibilities
- Operate and scale live agentic AI systems across Azure and GCP
- Build and maintain observability tooling for agent execution (logging, tracing, alerting)
- Implement auto-scaling for containerized agent workloads on Azure Container Apps, Cloud Run, and GKE
- Write and maintain production Python code for data pipelines and agent workflows
- Deploy and operate workflow orchestration using Prefect
- Write and maintain Terraform across Azure and GCP
- Build and maintain CI/CD pipelines and release management workflows
- Drive SLO/SLI frameworks and incident response
Requirements
- 3–5 years in software engineering, DevOps, MLOps, or platform engineering with production system ownership
- Strong Python engineering (production-grade code, packaging, containerization, dependency management)
LG
LaStellar Group
New York · US
LaStellar Group is a fintech company that operates a fast-growing platform, focusing on complex financial infrastructure and high-performance engineering. The company specializes in cloud architecture, site reliability engineering, CI/CD, and distributed systems, with a roadmap that includes developing infrastructure for AI workloads.
