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Application Tech Support Practitioner
Bengaluru
Job No. atci-5469291-s1997317
Full-time
Jobbeschreibung
Project Role : Application Tech Support Practitioner
Project Role Description : Act as the ongoing interface between the client and the system or application. Dedicated to quality, using exceptional communication skills to keep our world class systems running. Can accurately define a client issue and can interpret and design a resolution based on deep product knowledge.
Must have skills : Enterprise Systems Monitoring Tools
Good to have skills : Dynatrace Administration
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Primary Skill: Observability & AIOps
Secondary Skill: GenAI / Agentic AI for Operations
Role Summary
Responsible for leading the design, implementation, and operation of enterprise observability platforms, with a strong focus on AI driven, observability led operations.
Accountable for enabling reliable, scalable, and intelligent Run operations through observability, automation, AIOps, and agentic AI capabilities across client and enterprise environments.
Acts as a technical lead and force multiplier, enabling delivery teams to reduce noise, improve MTTR, and embed AI enabled operational workflows at scale.
Key Responsibilities
Resource needs to be AI Ready
Observability Platform Leadership
Lead end to end observability design and implementation across metrics, logs, traces, events, synthetics, and user experience
Provide hands on technical leadership across multiple enterprise observability platforms
Define and standardize cross tool observability frameworks to reduce fragmentation
Enable topology discovery, dependency mapping, and actionable dashboards for Ops, SRE, and leadership
AI, AIOps & Agentic Operations
Apply AIOps techniques including anomaly detection, event correlation, noise reduction, and predictive incident prevention
Leverage GenAI for operational use cases, including:
o Incident summarization
o Root cause analysis assistance
o Runbook generation
o Knowledge base enrichment
Design and operationalize agentic AI workflows (diagnostic, orchestration, remediation agents)
Enable semi automated and automated remediation through integrations and workflows
Automation & Engineering Enablement
Drive automation of deployments, health checks, upgrades, and routine operational tasks
Implement self healing and auto remediation workflows using automation and CI/CD integration
Embed observability and AI capabilities into cloud native and CI/CD architectures
Collaboration & Delivery Enablement
Partner with SRE, DevOps, Security, and Application teams to improve reliability and performance
Act as an enablement lead, coaching teams on observability, AI, and agentic operations
Translate technical signals into business relevant outcomes (stability, resilience, velocity)
Required Skills & Experience
Observability & Tools
7+ years hands on experience across multiple (3+) observability platforms, such as:
o Dynatrace
o Datadog
o New Relic
o Splunk (Enterprise / ITSI / Observability Cloud)
o Prometheus / Grafana
Strong knowledge of:
o Metrics, logs, traces, events
o Alerting strategies and noise reduction
o Topology and dependency mapping
o ITSM integrations (e.g. ServiceNow)
AI / GenAI / Agentic AI
Practical experience applying AIOps and ML for operations
Working knowledge of:
o LLM fundamentals
o Prompt engineering for Ops use cases
o AI assisted troubleshooting workflows
Experience or strong exposure to agent based / agentic AI models, including orchestration concepts
Cloud, Data & Automation
Strong knowledge of AWS / Azure / GCP, containers, Kubernetes, and microservices
Experience with telemetry pipelines, time series data, and streaming architectures
Proficiency in Python and/or Java/Go for automation and integrations
Experience with IaC and automation tools (Terraform, Ansible, Jenkins or equivalent)
Professional Skills
Strong client and stakeholder management capability
Structured problem solving and critical thinking
Ability to explain technical and AI concepts in business language
Outcome driven mindset focused on MTTR, noise reduction, and operational resilience
Career Level Expectations CL7
Operates independently with accountability for complex, cross platform initiatives
Acts as a technical authority within observability and AI enabled operations
Influences operating models combining human + AI + agent based workflows
Drives measurable outcomes rather than tool adoption alone
Success Measures
Reduced alert noise and manual operational effort
Improved MTTR and incident prevention through AI driven insights
Observability embedded into Run workflows, not standalone tooling
Delivery teams enabled to operate with reduced dependency on specialists
Project Role Description : Act as the ongoing interface between the client and the system or application. Dedicated to quality, using exceptional communication skills to keep our world class systems running. Can accurately define a client issue and can interpret and design a resolution based on deep product knowledge.
Must have skills : Enterprise Systems Monitoring Tools
Good to have skills : Dynatrace Administration
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Primary Skill: Observability & AIOps
Secondary Skill: GenAI / Agentic AI for Operations
Role Summary
Responsible for leading the design, implementation, and operation of enterprise observability platforms, with a strong focus on AI driven, observability led operations.
Accountable for enabling reliable, scalable, and intelligent Run operations through observability, automation, AIOps, and agentic AI capabilities across client and enterprise environments.
Acts as a technical lead and force multiplier, enabling delivery teams to reduce noise, improve MTTR, and embed AI enabled operational workflows at scale.
Key Responsibilities
Resource needs to be AI Ready
Observability Platform Leadership
Lead end to end observability design and implementation across metrics, logs, traces, events, synthetics, and user experience
Provide hands on technical leadership across multiple enterprise observability platforms
Define and standardize cross tool observability frameworks to reduce fragmentation
Enable topology discovery, dependency mapping, and actionable dashboards for Ops, SRE, and leadership
AI, AIOps & Agentic Operations
Apply AIOps techniques including anomaly detection, event correlation, noise reduction, and predictive incident prevention
Leverage GenAI for operational use cases, including:
o Incident summarization
o Root cause analysis assistance
o Runbook generation
o Knowledge base enrichment
Design and operationalize agentic AI workflows (diagnostic, orchestration, remediation agents)
Enable semi automated and automated remediation through integrations and workflows
Automation & Engineering Enablement
Drive automation of deployments, health checks, upgrades, and routine operational tasks
Implement self healing and auto remediation workflows using automation and CI/CD integration
Embed observability and AI capabilities into cloud native and CI/CD architectures
Collaboration & Delivery Enablement
Partner with SRE, DevOps, Security, and Application teams to improve reliability and performance
Act as an enablement lead, coaching teams on observability, AI, and agentic operations
Translate technical signals into business relevant outcomes (stability, resilience, velocity)
Required Skills & Experience
Observability & Tools
7+ years hands on experience across multiple (3+) observability platforms, such as:
o Dynatrace
o Datadog
o New Relic
o Splunk (Enterprise / ITSI / Observability Cloud)
o Prometheus / Grafana
Strong knowledge of:
o Metrics, logs, traces, events
o Alerting strategies and noise reduction
o Topology and dependency mapping
o ITSM integrations (e.g. ServiceNow)
AI / GenAI / Agentic AI
Practical experience applying AIOps and ML for operations
Working knowledge of:
o LLM fundamentals
o Prompt engineering for Ops use cases
o AI assisted troubleshooting workflows
Experience or strong exposure to agent based / agentic AI models, including orchestration concepts
Cloud, Data & Automation
Strong knowledge of AWS / Azure / GCP, containers, Kubernetes, and microservices
Experience with telemetry pipelines, time series data, and streaming architectures
Proficiency in Python and/or Java/Go for automation and integrations
Experience with IaC and automation tools (Terraform, Ansible, Jenkins or equivalent)
Professional Skills
Strong client and stakeholder management capability
Structured problem solving and critical thinking
Ability to explain technical and AI concepts in business language
Outcome driven mindset focused on MTTR, noise reduction, and operational resilience
Career Level Expectations CL7
Operates independently with accountability for complex, cross platform initiatives
Acts as a technical authority within observability and AI enabled operations
Influences operating models combining human + AI + agent based workflows
Drives measurable outcomes rather than tool adoption alone
Success Measures
Reduced alert noise and manual operational effort
Improved MTTR and incident prevention through AI driven insights
Observability embedded into Run workflows, not standalone tooling
Delivery teams enabled to operate with reduced dependency on specialists
Qualifikationen
15 years full time education
