AI Ops Engineer
OneMagnify (company site, opens in a new tab)3–5 yrsChennaiOn-siteDirect career pageEst. 12–22 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, automate, and operate end-to-end cloud and AI infrastructure including CI/CD pipelines, containerized microservices, observability, and platform guardrails for Generative AI applications.
- Architect and manage highly available, multi-service AI workloads on cloud platforms ensuring compute, storage, networking, and security lifecycle management.
- Collaborate with AI engineers and modelers to enable self-service tooling and automated workflows to facilitate safe, scalable, and reliable AI production deployments.
Minimum Requirements
- 3–5 years in cloud engineering, DevOps, or SRE with at least 1–2 years hands-on deploying and operating AI/ML/Generative AI in production.
- Bachelor's or Master's degree in Computer Science, Software Engineering, Cloud Computing, Data Engineering, or related technical discipline.
- Strong proficiency in cloud platforms (e.g., Google Cloud Platform), CI/CD tooling, containerization (Docker/Kubernetes), Infrastructure as Code (Terraform).
- Experience with AI-Ops/LLMOps pipelines, scripting (Python or Bash), and cloud security practices including IAM, secrets management, and compliance.
Ideal Candidate Profile
- Operates best in a complex cloud environment managing full AI/ML infrastructure lifecycle in production with high availability and security standards.
- Deeply experienced in AI/ML Ops tooling and pipelines for Generative AI, including monitoring for model drift and hallucination mitigation.
- Experienced in collaborating cross-functionally with AI engineers and analysts to build developer-friendly platforms and reliable automated workflows.