Job Summary

We are seeking a solid Site Reliability Engineer (SRE) to join our Monitoring & Operations team. The ideal candidate will be responsible for maintaining, monitoring, troubleshooting, and supporting Kubernetes clusters and servers hosting deployed data science/ML models across Windows and Linux environments, including on-premises infrastructure.

This role has a strong focus on production monitoring, incident management, infrastructure reliability, debugging, and operational support. The candidate should be comfortable working with distributed systems, Kubernetes, Docker, Windows/Linux servers, monitoring platforms such as Datadog, and CI/CD environments.

Experience with Python and data science/ML workloads is an added advantage; however, the primary emphasis is on SRE/DevOps, infrastructure management, Kubernetes operations, monitoring, and production support.

Key Responsibilities

- Monitor and support production applications and machine learning workloads running on Windows and Linux servers.
- Maintain and troubleshoot on-premises infrastructure, servers, Kubernetes clusters, and Docker containers.
- Manage and monitor Kubernetes clusters hosting ML/data science workloads.
- Ensure reliable deployment, availability, and operation of ML models and applications in production.
- Monitor infrastructure, applications, services, and system performance using Datadog and related monitoring tools.
- Configure and maintain monitoring dashboards, alerts, logs, and metrics.
- Investigate production incidents, identify root causes, and implement corrective and preventive actions.
- Troubleshoot issues across operating systems, containers, Kubernetes, networking, applications, and infrastructure.
- Participate in production support, incident management, escalation, and resolution.
- Automate repetitive operational tasks to improve reliability, scalability, and maintainability.




- Support CI/CD pipelines and application deployment processes.
- Ensure security, performance, availability, and reliability best practices are followed.
- Maintain operational documentation, system architecture documentation, deployment procedures, and troubleshooting/runbooks.
- Collaborate with software engineers, data scientists, DevOps teams, and business stakeholders to ensure smooth production operations.
- Continuously identify opportunities to improve system observability, automation, stability, and operational efficiency.

Required Qualifications

- Proven experience working with Windows and Linux operating systems in production environments.
- Hands-on experience with on-premises servers, Kubernetes, and Docker containers.
- Strong understanding of SRE, DevOps, and production operations practices.
- Hands-on experience with monitoring and observability tools, preferably Datadog.
- Strong troubleshooting and debugging skills across distributed systems and production environments.
- Experience with CI/CD pipelines and application deployment.
- Familiarity with AWS cloud services and infrastructure.
- Understanding of networking, system performance, logs, metrics, and alerts.
- Ability to analyze production incidents and perform root cause analysis (RCA).
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.




- Ability to work effectively in a monitoring/operations environment and handle production incidents with appropriate urgency.

Preferred Qualifications

- Experience supporting production machine learning/data science model deployments.
- Basic knowledge of Python for operational scripting and automation.
- Familiarity with ML model deployment and lifecycle concepts.
- Experience with OT/IT data integration or data bridging.
- Familiarity with Ignition for streaming robotics and PLC telemetry into cloud environments or enterprise databases.
- Experience with time-series databases and monitoring platforms such as:
- InfluxDB
- Prometheus
- AWS Timestream
- Familiarity with industrial/IoT environments, robotics, PLCs, or manufacturing systems is a plus.
- Experience with infrastructure automation and configuration management is an advantage.

Role: Monitoring & Operations

This is primarily a Monitoring, Operations, and Production Support role. The candidate will be expected to actively monitor production environments, respond to alerts and incidents, troubleshoot infrastructure/application issues, and maintain system reliability and availability.

Working Hours

- Shift Duration: 9.5 hours per day
- Time Zone: CST (Central Standard Time)
- Required CST Coverage: The candidate must be available to work at least until 2:00–2:30 PM CST
- The exact shift schedule will be finalized based on business and operational requirements.

What We Are Looking For

We are looking for someone who is hands-on, dependable, technically strong, and comfortable with production environments. The ideal candidate should be able to independently investigate alerts, troubleshoot issues across infrastructure and applications, communicate effectively during incidents, and continuously improve the reliability of production systems.

Pay: ₹900,000.00 - ₹1,200,000.00 per year

Work Location: Remote

📌 Site Reliability Engineer (SRE) – Monitoring & Operations (India)
🏢 Observance Solutions Private
📍 India