Introduction
Joining the IBM Technology Expert Labs teams means you’ll have a career delivering world-class services for our clients. As the ultimate expert in IBM products, you’ll bring together all the necessary technology and services to help customers solve their most challenging problems. Working in IBM Technology Expert Labs means accelerating the time to value confidently and ensuring speed and insight while our clients focus on what they do best—running and growing their business.Excellent onboarding and industry-leading learning culture will set you up for a positive impact, while advancing your career. Our culture is collaborative and experiential. As part of a team, you will be surrounded by bright minds and keen co-creators—always willing to help and be helped—as you apply passion to work that will positively impact the world around us.
Your Role And Responsibilities
We are looking for an experienced
IBM Middleware Engineer
with strong hands-on expertise in
IBM App Connect Enterprise (ACE)
,
IBM MQ
, and
Apache Kafka
to join our
24/7 operations team
.The role involves monitoring, incident resolution, troubleshooting, performance tuning, and ensuring high availability of middleware and integration platforms in mission-critical production environments.
Key Responsibilities
Operations & Support (Primary)
- Provide L2/L3 support for IBM ACE, IBM MQ, and Kafka platforms in a rotational 24/7 support model.
- Monitor system health, queues, message flows, Kafka brokers, topics, and connectors.
- Perform initial triage, root-cause analysis, and coordinate issue resolution.
- Handle production incidents, outages, and performance degradations with strict SLAs.
- Participate in on-call rotation and ensure timely response to alerts.
IBM App Connect Enterprise (ACE)
- Monitor and support ACE message flows, integration servers, bar deployments, and node runtime.
- Troubleshoot flow failures, mapping errors, ESQL issues, and performance bottlenecks.
- Work with developers for fix coordination and deployment activities.
IBM MQ
- Monitor and support queue managers, queues, channels, listeners, and cluster components.
- Handle dead-letter queues (DLQ), message failures, channel resets, and TLS certificate issues.
- Perform MQ object administration during maintenance windows.
Apache Kafka
- Monitor and support Kafka clusters, brokers, topics, partitions, and consumer groups.
- Handle connectivity issues, lag monitoring, offset resets, schema registry usage, and connector failures.
- Perform health checks and assist in scaling, tuning, and troubleshooting.
Maintenance & Continuous Improvement
- Execute scheduled maintenance, patching, certificate renewals, and system upgrades.
- Maintain runbooks, SOPs, and production documentation.
- Provide inputs for stability improvements and automation opportunities.
- Work with cross-functional teams for major incident handling and post-incident reviews.
Preferred Education
Master's Degree
Technical Skills
Required technical and professional expertise
- Strong hands-on knowledge of:
- IBM App Connect Enterprise (ACE V11/V12)
- IBM MQ (9.x or above)
- Apache Kafka (Confluent/Open-source)
- Good understanding of:
- Message flows, ESQL, mapping nodes
- MQSC commands, MQ clusters, MQ security
- Kafka Connect, Schema Registry, consumer lag, message retention
- Integration patterns: pub/sub, request-reply, async messaging
- Familiarity with:
- Linux/Unix environment
- Shell scripting (bash/ksh)
- Monitoring tools (Instana, Grafana, Splunk, ELK or similar)
- SSL/TLS certificates and security configurations
- CI/CD tools (Jenkins, Git, Tekton) – preferred
Professional Skills
- Strong analytical and troubleshooting abilities.
- Ability to handle pressure during critical incidents.
- Clear communication and documentation discipline.
- Strong ownership, accountability, and teamwork.
Preferred Technical And Professional Experience
- Experience with Kubernetes/OpenShift middleware deployments.
- Knowledge of IBM ACE development (ESQL/JavaCompute).
- Experience with event-driven architecture.
- Exposure to cloud (AWS, Azure, GCP).
