AI Infrastructure Engineer
About the Role
We’re hiring an AI Infrastructure Engineer to shape and scale the backend systems that power our AI platform. As a Series A company, your work will be foundational, enabling safe, efficient, and reliable AI workflows from end to end.
What You’ll Do
Design and implement scalable backend architectures tailored for AI workloads (inference, orchestration, monitoring).
Manage and optimize distributed job orchestration using Celery, Temporal, RabbitMQ, and Celery Beat.
Enhance data pipelines and caching strategies using Redis.
Collaborate closely with ML engineers to integrate models into production, ensuring scalability and reliability.
Build robust monitoring, observability, retry, and fault tolerance systems around job execution.
Support infrastructure management and incident response to ensure uptime and performance.
Contribute to platform infrastructure and tooling to support Stack AI’s rapid growth trajectory.
What We're Looking For
4+ years of backend engineering experience (Python preferred).
Deep expertise in task queues, job orchestration, and distributed systems.
Hands-on experience with Redis, Celery, RabbitMQ, Celery Beat, and ideally Temporal.
Experience scaling systems at a startup or in fast-paced environments.
Strong understanding of deploying, monitoring, and optimizing AI/ML systems in production (infrastructure toolsets and CI/CD practices)
Familiarity with containerization (Docker, Kubernetes), IaC (Terraform), or MLOps pipeline.
Why You’ll Love Working Here
Play a foundational role at a fast-growing Series A startup that is shaping the future of AI in enterprise workflows.
Collaborate across Product, ML, and Platform teams, be the bridge between AI logic and scalable execution.
Build infrastructure that enables real value for large enterprises: low-code, secure, and scalable AI workflows.Join a company that's scaling thoughtfully, values developer experience, and moves with agility.
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