Job Summary
Job SummaryWe are seeking a highly skilled Middleware & Agentic AI Platform Engineer to design, build, automate, and operate modern enterprise platforms across Middleware, Cloud, Kubernetes, DevOps, and AI ecosystems. The role combines traditional middleware expertise with emerging Agentic AI, automation, SRE, and cloud-native operations to drive intelligent, reliable, and self-healing enterprise platforms.Key Responsibilities
Middleware Engineering
Manage and support enterprise middleware platforms including API Management, Messaging, Integration, and Application Servers.
Design and implement highly available, scalable, and secure middleware architectures.
Perform performance tuning, troubleshooting, root cause analysis, and platform optimization.
Agentic AI & Automation
Design and implement AI-driven operational workflows and Agentic AI solutions.
Build intelligent automation for incident management, observability, and self-healing operations.
Develop AI-powered runbooks, copilots, and operational assistants.
Cloud & Kubernetes
Deploy and operate cloud-native applications on Azure, AWS, or GCP.
Manage Kubernetes/OpenShift platforms for containerized workloads.
Implement scalability, resiliency, and security best practices for cloud environments.
DevOps & SRE
Build and maintain CI/CD pipelines using modern DevOps practices.
Implement Infrastructure as Code (IaC) using Terraform, Ansible, or similar tools.
Drive observability, reliability engineering, proactive monitoring, and automation initiatives.
Platform Transformation
Lead modernization of legacy middleware platforms to cloud-native architectures.
Support migration, transformation, and operational excellence programs.
Contribute to innovation, reusable accelerators, and automation frameworks.
Required Skills
Middleware Technologies
IBM MQ
Apache Kafka
RabbitMQ / ActiveMQ
IBM ACE / IIB
MuleSoft
WebLogic, WebSphere, Tomcat, JBoss
API Gateways (Apigee, Kong, IBM APIC)
Agentic AI & GenAI
Agentic AI Concepts
Multi-Agent Frameworks (CrewAI, AutoGen, LangGraph)
Prompt Engineering
RAG Architecture
MCP Integration
LLM Platforms (OpenAI, Azure OpenAI, Claude, Groq)
Cloud & Kubernetes
Azure / AWS / GCP
Kubernetes / OpenShift
Docker Containers
Cloud Networking & Security
DevOps & Automation
GitHub / GitLab
Jenkins / Azure DevOps
Terraform
Ansible
Python Scripting
CI/CD Automation
Observability & SRE
Dynatrace
Grafana
Prometheus
ELK Stack
Splunk
Site Reliability Engineering Practices
Preferred Qualifications
5–12 years of experience in Middleware, Cloud, or Platform Engineering.
Certifications in Kubernetes, Cloud, Middleware, or DevOps.
Experience delivering enterprise transformation programs.
Exposure to AI/Agentic AI implementations in IT Operations.
Key Responsibilities
2. To perform value addition activities (such as mentoring administrators/team members, preparing SOPs, maintaining effective documentation simultaneously and Knowledge sharing.) In addition act as a liaison to the business segment, facilitating effective communication and presentation to key business stakeholders as & when required.
3. To validate Change Order Implementation Plan & Human Error Compliance and participate in Capacity planning, identification of EN business opportunities.
4. To ensure positive customer feedback & satisfaction through active participation in customer meetings to understand any issues faced
5. To validate analyses (eg. Root Cause Analysis ,Trend Analysis) and reports to facilitate performance in tasks to be presented to key business stakeholders