Observability Engineer

Job Summary

We are looking for an experienced Observability Engineer with strong expertise in ThousandEyes, Splunk, database technologies, and Python automation. The candidate will be responsible for monitoring application, network, and infrastructure performance, identifying issues, and developing automation solutions to improve system visibility, reliability, and operational efficiency.

Required Skills

• Observability
• ThousandEyes / Cisco ThousandEyes
• Splunk
• OracleDB
• MongoDB
• SQL
• Python Automation

Roles & Responsibilities

• Implement and support observability and monitoring solutions across applications, networks, and infrastructure.
• Work with ThousandEyes for network and digital experience monitoring.
• Configure and maintain monitoring dashboards, alerts, and performance metrics.
• Use Splunk for log analysis, monitoring, troubleshooting, and reporting.
• Work with OracleDB, MongoDB, and SQL for data analysis and troubleshooting.
• Develop Python scripts for monitoring and operational automation.
• Analyze performance issues and identify root causes across applications and infrastructure.
• Collaborate with application, infrastructure, and network teams to resolve incidents.
• Improve monitoring, alerting, and automation processes.
• Prepare performance and monitoring reports and provide actionable insights.

Mandatory Skills

• 7+ years of relevant experience
• Strong experience in Observability / Monitoring
• Hands-on experience with ThousandEyes
• Splunk
• Python Automation
• SQL
• OracleDB / MongoDB

Job Summary

We are looking for a Senior Observability Engineer with strong expertise in ThousandEyes, Splunk, and Monitoring & Observability Engineering. The candidate should have experience implementing and enhancing monitoring solutions, along with basic Python automation scripting.

Primary Skills

• ThousandEyes
• Splunk
• Monitoring & Observability Engineering
• Oracle Database
• SQL
• MongoDB
• Python Automation

Key Responsibilities

• Implement, configure, and enhance enterprise monitoring and observability solutions.
• Work extensively with ThousandEyes for network and application performance monitoring.
• Develop and maintain monitoring dashboards, alerts, and reports using Splunk.
• Monitor application, infrastructure, network, and database performance.
• Work with Oracle Database, SQL, and MongoDB for monitoring and troubleshooting.
• Develop basic Python automation scripts to improve monitoring and operational efficiency.
• Analyze performance issues and support troubleshooting and root cause analysis.
• Collaborate with application, infrastructure, network, and database teams to resolve observability-related issues.
• Continuously improve monitoring coverage, alerting, and operational processes.

Secondary Skills

• GenAI Concepts
• SaaS Architecture Concepts
• Cloud Application Architecture

Ideal Candidate Profile

• 7+ years of experience in Observability / Monitoring Engineering.
• Strong hands-on experience with ThousandEyes and Splunk.
• Good understanding of databases including Oracle, SQL, and MongoDB.
• Basic hands-on experience with Python automation.
• Understanding of application, infrastructure, and network monitoring.
• Exposure to GenAI, SaaS, or Cloud Application Architecture is an added advantage.

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow

Job Summary 

A Senior Full Stack Observability Engineer – AI Ops & Autonomous Observability to handle / manage , Design and implement enterprise-wide observability across applications, infrastructure, cloud, network, database and digital services. Lead adoption of Datadog, AI Ops, SRE and Autonomous Observability. Build agentic AI and multi-agent orchestration solutions that automate operational workflows and enable autonomous operations.

Technical Skills

• Datadog (Expert)
• OpenTelemetry
• Distributed Tracing
• Application Performance Monitoring
• AI Ops
• LangGraph/CrewAI/AutoGen/Semantic Kernel
• Python
• Azure, AWS
• Kubernetes
• ServiceNow Integration
• 
  

Enterprise Observability Strategy

• Define observability standards, governance and operating model.
• Create monitoring roadmaps, service health frameworks, business service dashboards and dependency mapping.
• 
  

Full Stack Observability Scope

• Applications, APIs, microservices and user journeys.
• Windows, Linux, VMware, storage and infrastructure platforms.
• Azure and AWS.
• Network monitoring, SQL and NoSQL databases.
• 
  

Datadog Platform

• Deploy and optimize Datadog solutions.
• Build dashboards, monitors, alerts and observability-as-code frameworks.
• Integrate Datadog with ServiceNow, Teams and enterprise tooling.
• New Relic exposure is optional.
• 
  

AI Ops Responsibilities

• Event correlation and noise reduction.
• Predictive analytics and anomaly detection.
• Incident intelligence and root cause analytics.
• Proactive issue identification and MTTR reduction

Very strong infra engineer to administer Linux based VMs (and few Windows VMs as well).

Must have strong knowledge and hands-on on docker, Kubernetes

Must be good at monitoring (AppDynamics, Prometheus, Grafana) and logging (Splunk)

Develop automation scripts using Shell and Python. Must have good knowledge in Ansible.

Should be good at optimize/finetune server configurations.

 Should be good in troubleshoot issues and fix them.

L2 Production Support, Event Management / Mission Control, Incident Management, Linux, Linux, observability, and batch monitoring

Position Overview 

The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems. 

Responsibilities 

• Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms 
• Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning 
• Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection 
• Deploy, maintain and monitor containerized ML workloads 
• Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows 
• Implement AI-driven data validation, schema and concept drift detection and metadata management. 
• Establish governance frameworks for AI systems, including bias detection, explainability, and auditability 
• Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention 
• Develop automated test suites for model performance, regression, edge cases and bias validation 
• Monitor model KPIs (accuracy, precision, recall, latency, calibration) 
• Ensure reproducability of experiments and production models 
• Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption 

Qualifications 

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field 
• 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering 
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure 
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn 

Job Summary:

We are looking for a Senior SRE/DevOps Engineer with strong experience in site reliability, automation, monitoring, observability, and production support. The candidate will be responsible for ensuring the reliability, availability, security, and performance of enterprise platforms.

Key Responsibilities:

• Own reliability, availability, security, and performance of enterprise browser platforms.
• Manage access and identity controls, Group Policy, and SAML/SSO integrations.
• Handle CI/CD deployments, configuration management, monitoring, and health checks.
• Develop automation and operational workflows using Python and Bash.
• Perform performance monitoring and production troubleshooting.
• Implement and maintain observability frameworks.
• Work with monitoring tools such as Datadog, Splunk, Dynatrace, Prometheus, and Grafana.
• Participate in incident management, RCA, and continuous improvement activities.
• Support highly available production environments in a 24/7 shift model.
• Collaborate with application, infrastructure, security, and operations teams.

Mandatory Skills:

• 10+ years of experience in SRE / DevOps.
• Strong hands-on experience in Python and Bash scripting.
• Experience with CI/CD and configuration management.
• Strong knowledge of monitoring and observability.
• Hands-on experience with Datadog, Splunk, Dynatrace, Prometheus, or Grafana.
• Experience with SAML/SSO, Identity & Access Management, and Group Policy.
• Banking domain experience.

Mandatory Skills: L2 Production Support, Event Management / Mission Control, Incident Management, Linux, Linux, observability, and batch monitoring

Primary Skills:

• L2 Production Support, Event Management / Mission Control, ServiceNow, Production Monitoring, Splunk / AppDynamics / ThousandEyes