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DevOps Cloud Engineer

DevOps Cloud Engineer

Vellstoneindia, India
1 day ago
Job description

Job Description

Job Title : DevOps Cloud Engineer

Location : Noida / Onsite

Experience : 1–2 years

Qualification : B.E. / B.Tech in Engineering (Computer Science / IT / ECE preferred)

Work Schedule : Mon - Fri (Onsite)

We’re seeking a DevOps Cloud Engineer to manage our cloud infrastructure and CI / CD pipelines at IndiqAI, an agentic-AI native company focused on creating scalable, secure, enterprise-grade solutions that let humans and machines co-create in any language.

As the DevOps Cloud Engineer, your responsibilities would be :

  • Manage and optimize DevOps processes and cloud infrastructure.
  • Set up and manage applications on the cloud.
  • Build and manage CI / CD pipelines from local to cloud to pre-production.
  • Use Jenkins for automation and GitHub for version control.
  • Contribute to architecture design and scaling systems.
  • Write Python scripts for automation and monitoring.

Requirements

  • 1–2 years of DevOps / cloud engineering experience.
  • Strong hands-on experience with AWS, with exposure to Azure / GCP being a plus.
  • Knowledge of Jenkins, GitHub, and CI / CD pipelines.
  • Proficiency with containerization technologies like Docker and orchestration platforms like Kubernetes.
  • Strong Python programming skills are mandatory.
  • Exposure to cloud architecture / design.
  • Benefits

  • Work at IndiqAI, an AI-native company born in India and built for the world.
  • Get hands-on experience in a fast-paced AI environment.
  • Manage and optimize cloud infrastructure and CI / CD pipelines.
  • Contribute to the architecture and scaling of systems.
  • Gain experience with cutting-edge technologies like voice biometrics and AI-powered platforms.
  • Requirements

    Strong skills in SQL and PL / SQL, with experience in tuning slow queries. Proficiency in analyzing execution plans using tools like EXPLAIN, ANALYZE, and auto-explain. Expertise in indexing strategies, VACUUM / ANALYZE, and table partitioning. Skill in using monitoring views such as pg_stat statements, pg_stat activity, and pg_stat user tables. Knowledge of key PostgreSQL configuration parameters like work_mem and shared_buffers. Experience with connection pooling tools (e.g., PgBouncer) and managing locks and concurrency. Familiarity with schema optimization, normalization, and scalable data models. Comfort with PostgreSQL on AWS RDS and managing read replicas.

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