DevOps / Platform Engineer

New

Smart WorkingCybersecurity platform

India / Delhi NCR / Indore / Bangalore / Hyderabad / Chandigarh / Pune, UK working hoursFull-TimeMiddle

Salary not disclosed

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Job Details

Have hands-on experience managing production cloud infrastructure using AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Have practical experience with Infrastructure as Code (IaC), using Terraform or equivalent technologies.
Have hands-on experience with Docker and containerised environments.
Have proven ownership of CI/CD build, deployment, and release processes.
Have experience implementing and managing observability, incident response, and rigorous security practices.
Use AI agents and frontier AI models hands-on in engineering workflows.
Use LLMs and AI agents autonomously to learn unfamiliar technologies, navigate unfamiliar codebases, and manage multiple projects.
Be able to own engineering projects from start to finish.
Be willing to communicate directly with customers and own solutions through resolution of customer problems.
Be able to set priorities independently, reprioritise work, and deliver results without close supervision.
Communicate and collaborate consistently, and explain technical decisions and implementation approaches clearly.
Be able to work remotely during UK working hours.
Nice to have: experience with Microsoft Azure, ClickHouse or other data-intensive platforms, production LLM or AI agent workloads, Python or Go scripting, or SOC 2, GDPR, or other regulated environments.

Run, maintain, and scale production cloud infrastructure for a platform processing terabytes of data daily.
Own build, deployment, and release pipelines for Python, C++, and TypeScript applications.
Build and manage production infrastructure for AI agents, including observability, guardrails, and cost controls.
Own observability and incident response to maintain platform reliability.
Automate repetitive operational work using AI agents.
Take infrastructure and platform engineering projects from identifying requirements through delivery.
Manage multiple priorities, including major projects and smaller AI-driven tasks, while collaborating with the team.

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