Application Support Engineer

About Client : Our client is prominent Indian multinational corporation specializing in information technology (IT), consulting, and business process services and its headquartered in Bengaluru with revenues of gross revenue of ₹222.1 billion with global work force of 234,054 and listed in NASDAQ and it operates in over 60 countries and serves clients across various industries, including financial services, healthcare, manufacturing, retail, and telecommunications. The company consolidated its cloud, data, analytics, AI, and related businesses under the tech services business line. Major delivery centers in India, including cities like Chennai, Pune, Hyderabad, and Bengaluru, kochi, kolkata, Noida.Job Title : Application support Engineer

• Location : Pan India
• Experience : 6+Interview Date : 20 Sep 25
• Mode of Work : Hybrid
• Job Type : Contract to hire.
• Notice Period : Immediate joiners.
• Project Tenure : Long-term projectJob Description : AI / ML Integration in Support
• consider that in the primary skills
• Technical Expertise : 8-12 years of experience in Enterprise Application Support Management, with proficiency in automation, observability, and shift-left processes.
• Communication and Problem-Solving : Excellent verbal and written communication skills, attention to detail, and the ability to communicate effectively with stakeholders at all levels.
• Preferred Experience : Familiarity with Supply Chain domain, Service Now for Incident Management, and observability / monitoring tools like PagerDuty, Data-dog, Prometheus, and Splunk.
• Technical Leadership : Lead innovation in support with cutting-edge AI and LLM-powered tools, and act as technical lead during critical incidents.
• Support Process Improvement : Develop automation for auto-triage, self-healing, real-time diagnostics, and enhance observability platforms for early anomaly detection.
• Smart Support Tools Development : Contribute to building smart support tools like AI / ML summarizers, chatbots, and knowledge search systems, and integrate LLM-based agents into workflows.PrimaryEnterprise application support managementMonitoring and observability tools : PagerDuty, Datadog, Prometheus, SplunkIncident management platforms : ServiceNow, Jira Service ManagementExpertise in leveraging Automation & AI Tools to drive efficiency in technical supportSecondary ( Good to have )AI / ML Integration in Support – Experience building smart support tools like chatbots, summarizers, and LLM-based agentsExperience with cloud platforms : AWS, GCP, AzureDevOps practicesContainerization : DockerOrchestration : Kubernetes