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About the Role
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Turium AI is building the next generation of intelligent automation systems for enterprises. We are looking for a Software Engineer with strong DevOps skills and hands-on backend experience working with
Python-based low-code ERP frameworks
, microservices, and cloud deployments.
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You will work closely with our engineering and product teams to enhance our platform, build integrations, automate workflows, and ensure reliable deployments.
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Key Responsibilities:
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Platform Engineering
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Develop and maintain backend modules on a
Python-based low-code ERP framework
.
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Build APIs, custom scripts, server-side logic, and workflow automations.
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Integrate internal and third-party systems used across Turium AI’s operations.
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Optimize backend performance, caching, and data models.
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DevOps & Infrastructure
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Manage CI/CD pipelines (GitHub Actions / GitLab CI / Jenkins).
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Deploy and maintain services across cloud platforms (AWS / GCP / Azure).
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Provision, monitor, and scale containerized applications using
Docker & Kubernetes
.
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Implement best practices for system reliability, logging, and observability.
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Automate infrastructure using Terraform/Ansible (or similar tools).
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Security & Reliability
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Ensure role-based access, data protection, and secure API communication.
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Perform environment hardening, secrets management, and vulnerability mitigation.
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Required Skills
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~3 years of experience in backend engineering plus DevOps.
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Strong proficiency in
Python
and server-side development.
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Hands-on experience building modules on
any Python-based low-code ERP or rapid-development framework
(e.g., form builders, DocTypes, workflow engines).
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Solid knowledge of
Linux environments
, shell scripting & server administration.
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Experience with:
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Docker, Kubernetes
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Git, CI/CD
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Cloud infrastructure (AWS/GCP/Azure)
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Redis / MariaDB / PostgreSQL
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Understanding of event-driven architecture, webhooks, and background jobs.
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Good to Have
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Familiarity with AI/ML workflows or model integration.
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Experience building internal tools for teams (Ops, Sales, Finance, Engineering).
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Background in scaling distributed systems.
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Exposure to task queues, caching layers, and async workers.
