Dynatrace Support Engineer

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
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Enterprise Observability Strategy

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

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

We are looking for an experienced SRE / DevOps Engineer with strong expertise in production support, site reliability engineering, cloud infrastructure, automation, and monitoring. The candidate should have experience maintaining highly available systems, troubleshooting production issues, and improving infrastructure reliability and performance.

Mandatory Skills

• Site Reliability Engineering (SRE)
• DevOps Engineering
• Production Support
• Linux Administration
• Cloud Infrastructure (AWS / Azure / GCP)
• Kubernetes and Docker
• CI/CD pipelines
• Monitoring and Observability
• Scripting using Python / Shell
• Incident Management and Root Cause Analysis

Key Responsibilities

• Monitor and maintain the availability, reliability, and performance of applications and infrastructure.
• Handle production incidents, troubleshoot issues, and perform root cause analysis.
• Manage and automate infrastructure deployment and operational tasks.
• Work with CI/CD pipelines and container orchestration platforms.
• Implement monitoring, alerting, and observability solutions.
• Collaborate with development and operations teams to improve system reliability.
• Support cloud infrastructure, Linux environments, and production deployments.
• Identify recurring issues and implement preventive measures to reduce downtime.

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

Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.

Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.

Key Responsibilities:

Architecture & Platform

• Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
• Lead IaC standards and reusable modules org-wide; own GitOps practices
• Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration

Reliability Engineering

• Define and drive reliability targets (SLOs/SLIs); establish SRE practice
• Lead incident management, RCA, and blameless post-mortems for critical systems
• Partner on infrastructure hardening and compliance (SOC 2, HIPAA)

AI-First Engineering

• Lead AI/ML inference and GPU infrastructure scaling in production
• Evaluate and introduce AI tooling, platforms, and automation best practices
• Contribute to LLM deployment pipelines and AI systems reliability

Leadership & SDLC

• Mentor L1/L2 engineers; influence cross-team infrastructure decisions
• Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
• Evaluate and introduce new tooling and platforms

Key Requirements:

• 4–8 years infrastructure/platform/DevOps/SRE
• Deep expertise in AWS & GCP large-scale production systems
• Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
• AI/ML inference or GPU infrastructure scaling (production track record)
• Strong Terraform / equiv. and GitOps practices
• Python, Go, or Bash scripting and automation
• Track record in scale, reliability, and cost efficiency
• Lead incident response and on-call practices

Nice-to-Have

• LLM Gateway architecture and optimization
• Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
• DevSecOps maturity: SBOM, supply-chain security, policy-as-code
• Open-source contributions or platform-team leadership

Why This Role?

• Build infrastructure and products powering real-world healthcare AI
• Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
• Mission-driven impact — improve patient outcomes and save thousands of staff hours
• High ownership, rapid learning, and significant career upside
• Global collaboration across India and the US
• Seed-stage growth — scale from Seed to Series A alongside the team
• Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering

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

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 Description

Role: Site Reliability Engineer (SRE)

Experience: 8+ Years

Location: Bangalore

Notice Period: Immediate Joiners Only

Key Responsibilities

• Implement reliability practices across applications and cloud platforms.
• Monitor and troubleshoot production systems using observability tools.
• Manage incidents, perform root cause analysis (RCA), and prepare post-incident reports.
• Develop and maintain CI/CD pipelines and automate operational tasks.
• Improve system availability, performance, scalability, and operational stability.
• Develop proof-of-concepts and convert them into production-ready solutions.
• Collaborate with engineering teams to improve reliability and reduce operational toil.
• Use AI tools responsibly to enhance operational efficiency and productivity.

Required Skills

• Strong SRE fundamentals and production support experience.
• Hands-on experience with AWS cloud services and best practices.
• Observability tools: Splunk, Grafana, and Datadog.
• Understanding of metrics, logs/events, and distributed tracing.
• Familiarity with Amazon Connect and contact center technologies, including voice, call recording, and telephony.
• CI/CD tools: Jenkins/Jules; source control: Git/Bitbucket.
• Scripting and automation skills are preferred.
• Experience in incident management, troubleshooting, and RCA documentation.
• Cloud certification or experience supporting cloud-based applications.
• Familiarity with AI concepts and responsible AI tool usage.

Role Overview

We are looking for an experienced Application Support Engineer with strong expertise in production support, Linux/Unix troubleshooting, Oracle database support, and monitoring tools. The candidate should have experience managing critical production environments, resolving technical issues, and maintaining application stability and availability.

Key Responsibilities

• Provide end-to-end production support for business-critical applications.
• Troubleshoot application, server, and database-related issues in Linux/Unix environments.
• Perform Oracle SQL queries, database troubleshooting, and performance analysis.
• Manage incidents, service requests, and change management processes.
• Conduct RCA for recurring and critical production issues.
• Monitor application health and performance using Splunk, Grafana, and AppDynamics.
• Support applications hosted on cloud and container platforms such as OCP, AWS, Azure, and GCP.
• Collaborate with infrastructure, database, and development teams for issue resolution.
• Maintain operational documentation and ensure adherence to SLA commitments.

Technical Skills

• Application Production Support
• Linux / Unix Administration and Troubleshooting
• Oracle SQL / Database Support
• Incident, Problem & Change Management
• Root Cause Analysis (RCA)
• Splunk / Grafana / AppDynamics
• Cloud Platforms – OCP, AWS, Azure, GCP