About the Role

We are seeking an AI Infrastructure Engineer (Python) to support, scale, and enhance a production AI and data platform. This role sits at the intersection of AI infrastructure, cloud engineering, and agent-based systems.

You will be responsible for ensuring the reliability, scalability, and performance of AI-driven systems operating in production environments across multi-cloud platforms (Azure and GCP). This is not a modeling or research role it's focused on building and maintaining the infrastructure that powers AI systems at scale.

This is an excellent opportunity for someone with strong foundational engineering skills who is eager to deepen their expertise in AI platforms and cloud-native systems.

What You’ll Do

Systems Engineering & Agent Operations

Develop, maintain, and optimize production-grade Python code supporting data pipelines, agent workflows, and platform tooling
Own the full lifecycle of Python services (containerization, deployment, versioning, runtime management)
Manage environment configurations, secrets injection, and dependency management across containerized services
Build internal Python tooling and shared libraries to accelerate development workflows
Troubleshoot production issues end-to-end across application and infrastructure layers

AI Platform & Scaling

Operate and scale AI-driven agent systems in production environments
Ensure high availability, performance, and resilience under load
Support integrations between AI agents and data platforms
Build observability tools (logging, monitoring, tracing, alerting)
Implement auto-scaling strategies for containerized workloads
Contribute to evaluation frameworks and quality standards for AI systems

Infrastructure & Cloud Operations

Develop and manage infrastructure using Terraform across Azure and GCP
Manage cloud services including container registries, identity systems, secrets management, and networking
Deploy and maintain workflow orchestration tools (e.g., Prefect)
Maintain CI/CD pipelines and release workflows
Document systems, workflows, and data lineage with clear runbooks

What We’re Looking For

Required

3–5 years of experience in Software Engineering, DevOps, or MLOps
Strong Python skills with experience building production systems
Experience with Docker and containerized applications in cloud environments (Azure and/or GCP)
Hands-on experience with Terraform
Experience with secrets management tools and secure configuration practices
Familiarity with CI/CD pipelines and Git-based workflows
Strong troubleshooting and systems-thinking mindset
Interest in AI systems and infrastructure

Preferred

Experience with Azure services (Container Apps, ACR, Key Vault, Managed Identities, VNets)
Experience with GCP services (Cloud Run, GKE, Vertex AI, IAM, Secret Manager)
Familiarity with workflow orchestration tools (e.g., Prefect)
Exposure to AI/agent frameworks (e.g., LangChain, MCP)
Experience with observability tools (e.g., MLflow, Langfuse)
Experience with data tools such as dbt or Snowflake
Familiarity with multi-cloud environments

Fresh Jobs. Delivered to Your Inbox.

Engage Partners Inc. jobs

AI/ML Developer (Python)