What are the responsibilities and job description for the AI/ML Developer (Python) position at Engage Partners Inc.?
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
Salary : $150,000 - $250,000