Auric AI Labs DevOps Engineer Job in Bengaluru/Mumbai: Apply Now
Auric AI Labs
View All Jobs from Auric AI Labs →Auric AI Labs is actively hiring a technical professional to co-manage and strengthen their on-premises, network, and cloud environments. If you are looking for a DevOps Engineer Job, this onsite role in Bengaluru or Mumbai offers a fantastic opportunity to mature a growing platform through improved observability, automated deployments, and robust CI/CD practices. You will focus on core infrastructure while steadily increasing your footprint in MLOps as machine learning workflows move toward production.
This position requires 1+ years of hands-on experience in systems administration, SRE, or infrastructure-focused roles. The core tech stack involves Linux server administration, Docker containerization, and scripting in Bash or Python, alongside major cloud platforms like AWS, GCP, or Azure. You will also be expected to utilize infrastructure-as-code and CI/CD tools to reduce manual operational work.
Quick Job Details
What You'll Do
As a DevOps Engineer, your primary responsibilities will include managing server infrastructure and designing automated deployment pipelines.
- Co-manage server infrastructure: provisioning, hardening, patching, backups, and access management.
- Support firewall and network security operations: rule management, VPN access, segmentation, and anomaly monitoring.
- Administer cloud resources: services, IAM, cost monitoring, and security configuration.
- Design and implement CI/CD pipelines for automated testing and deployment.
- Introduce infrastructure-as-code to make environments reproducible and well-documented (Terraform, Ansible, or similar).
- Establish observability across servers, network, and applications: metrics, logging, alerting, and dashboards.
- Reduce manual operational work through automation.
- Support ML workflows with pipeline automation, experiment tracking, and model deployment tooling.
- Containerize and serve models, with monitoring for model and data health.
- Contribute to establishing reproducible, versioned ML practices.
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What You Need (Requirements)
To qualify for this infrastructure and automation role, candidates must meet the following experience and technical skill requirements.
- 1+ years of hands-on experience in DevOps, systems administration, SRE, or infrastructure-focused roles.
- Working knowledge of networking and network security: firewalls, VPNs, DNS, TLS, ports/protocols, and hardening practices.
- Experience administering Linux servers (provisioning, users and permissions, services, troubleshooting).
- Familiarity with at least one major cloud provider (AWS, GCP, or Azure).
- Experience with containers (Docker) and scripting (Bash and/or Python).
- Exposure to CI/CD concepts and tooling (GitHub Actions, GitLab CI, Jenkins, etc.).
- Interest in MLOps and willingness to learn the ML lifecycle: training pipelines, model deployment, and monitoring.
- Strong ownership mindset and clear communication around security and reliability trade-offs.
- Nice to have: Experience managing on-premises infrastructure (physical servers, local networking, hypervisors).
- Nice to have: Hands-on exposure to MLOps tooling (MLflow, Kubeflow, Airflow, model serving frameworks).
- Nice to have: Infrastructure-as-code experience (Terraform, Ansible, Pulumi).
- Nice to have: Kubernetes or other container orchestration experience.
- Nice to have: Monitoring and observability stack experience (Prometheus, Grafana, Loki, ELK).
- Nice to have: GPU workload or ML infrastructure exposure.
- Nice to have: Relevant certifications (cloud provider associate-level, networking, or security).
Tech Stack
💡 Gigsdock Pro-Tip
To stand out for this DevOps Engineer Job, make sure your resume highlights your hands-on experience with Linux server administration, Docker containerization, and CI/CD pipelines like GitHub Actions or Jenkins. During your technical interview, be prepared to discuss how you balance network security (firewalls, VPNs, DNS) with infrastructure automation, and showcase any familiarity you have with Infrastructure-as-Code (Terraform or Ansible). Since Auric AI Labs is transitioning machine learning workflows to production, expressing a strong interest in or showcasing basic exposure to MLOps tooling like MLflow or Kubeflow will give you a significant advantage.
⚠️ Disclaimer & Important Information
- Never pay any amount for getting a job. Genuine employers never charge recruitment fees.
- Apply before the hiring closes or the employer stops accepting applications.