ApplySarthi

DevOps / Platform Engineer

Jobgether

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What platform roles keep asking for: Observability (37%), Python (35%), AWS (31%), Kubernetes (30%), CI/CD (27%), System design (24%), Azure (18%), GCP (18%) — counted across their open postings here.

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Interviews for platform roles keep coming back to Observability, Python, AWS, Kubernetes. Practise those questions before you sit with Jobgether.

Questions you are likely to be asked

  1. Why do you want to join Jobgether?
  2. What is your experience with Azure? Tell me one thing you learned the hard way.
  3. How do you keep secrets and access safe in your infrastructure?
  4. Walk me through how code gets from a commit to production where you work.
  5. Tell me about an outage you handled. What did you learn from it?

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Accountabilities: As a DevOps / Platform Engineer, you will be responsible for the reliability, scalability, and continuous improvement of production infrastructure. You will own projects from initial requirements through implementation and delivery, collaborating with engineering colleagues and customers to achieve meaningful results. Your responsibilities will include: Run, maintain, and scale production cloud infrastructure supporting a platform that processes terabytes of data daily. Own build, deployment, and release pipelines for Python, C++, and TypeScript applications. Design, build, and manage production infrastructure for AI agents, incorporating observability, guardrails, and cost controls. Lead observability practices and incident response activities to maintain platform reliability. Automate repetitive operational tasks and workflows using AI agents. Take end-to-end ownership of infrastructure and platform engineering projects, from identifying requirements to delivering solutions. Manage multiple priorities, including major engineering projects and smaller AI-driven initiatives. Communicate effectively with engineering teams and customers, ensuring technical issues are understood and resolved. Identify opportunities to improve infrastructure, engineering processes, and operational efficiency. Make informed decisions about priorities and adapt quickly to changing requirements while maintaining delivery quality. Requirements The ideal candidate is a technically strong, autonomous engineer who combines hands-on cloud infrastructure expertise with a proactive approach to problem-solving. You should be comfortable taking responsibility for complex projects, using AI tools as part of your daily workflow, and delivering results in a collaborative remote environment. The following qualifications and competencies are expected: Extensive hands-on experience managing production cloud infrastructure using AWS, Microsoft Azure, or Google Cloud Platform (GCP). Practical experience with Infrastructure as Code (IaC), particularly Terraform or equivalent technologies. Strong experience with Docker and containerized environments. Proven ownership of CI/CD pipelines, including build, deployment, and release processes. Experience implementing and managing observability, incident response, and robust security practices. Daily, hands-on experience using AI agents and advanced AI models in engineering workflows. Ability to use LLMs and AI agents independently to learn unfamiliar technologies, navigate new codebases, and manage multiple projects effectively. Demonstrated ability to own engineering projects from conception through delivery, rather than focusing solely on assigned tickets. Strong customer focus, including the ability to communicate directly with customers and take responsibility for resolving their problems. High sense of urgency and sound judgment when reprioritizing work to maximize impact. Ability to set priorities, make decisions, and deliver results independently without close supervision. Strong communication and collaboration skills, with the ability to explain technical decisions and implementation approaches clearly. Growth mindset, openness to constructive feedback, and willingness to rethink existing code or approaches when necessary. Trustworthy and accountable working style, with strong attention to detail and the ability to identify and communicate problems early. Availability to work remotely during UK business hours. Nice to Have Experience with Microsoft Azure, particularly in cloud migration initiatives and Azure Marketplace integration. Familiarity with ClickHouse or other data-intensive platforms. Experience operating LLM or AI agent workloads in production environments. Scripting experience with Python or Go. Familiarity with SOC 2, GDPR, or other regulated environments. Benefits Fully remote, long-term employment opportunity. Opportunity to work on an AI-native cybersecurity platform operating at significant data scale. High degree of autonomy and end-to-end ownership of engineering projects. Collaboration with a multidisciplinary international engineering team. Exposure to advanced AI agents, cloud infrastructure, and modern platform engineering practices. Opportunity for professional growth in a remote-first environment that values employee development and well-being.

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Listed on lever · posted 2026-11-04. ApplySarthi collects openings and links to application pages; the role is advertised by Jobgether, not by us.