Contribute to a developer-first platform with strong focus on usability and reliability
Drive automation-first engineering using Infrastructure-as-Code and GitOps
Operate Kafka at Scale
Operate Kafka clusters on Kubernetes (AKS/EKS) and on-prem (VM/bare-metal)
Own
Topic design, partitioning, replication strategy
ISR management and broker health
Performance tuning (throughput, latency, storage)
Support hybrid patterns (on-prem ↔ cloud connectivity, replication, migration)
AI-Driven Operations
Apply AI/ML techniques for
Anomaly detection and predictive alerting
Faster incident triage and root cause insights
Automated remediation (AIOps)
Use AI tools to accelerate Debugging, Runbook creation and Operational automation
Observability & Reliability Engineering
Define and track SLIs/SLOs and error budgets
Build and monitor observability using Prometheus, Grafana, Loki
Drive proactive reliability and blameless postmortems
Operational Excellence
Improve reliability through
Automation and failure testing
Strong runbooks and incident response
Participate in on call with focus on prevention over reaction
Ensure robust change management and pre-prod validation
Cost & Efficiency
Optimize infrastructure and network cost across cloud and on-prem
Right-size Kafka clusters and improve utilization
Provide cost and usage visibility to platform users
Collaboration
Work with product, SRE, network, and security teams
Guide teams on event streaming best practices
Contribute to platform roadmap and architecture decisions
What We’re Looking For
Must Have
Core Requirements
3–8 years in Platform Engineering / SRE / Software Engineering
Strong hands-on experience operating Apache Kafka in production
Deep understanding of the Kafka ecosystem (Kafka Connect, MirrorMaker, Schema Registry etc) and practical experience operating and optimizing data streaming platforms at scale
Strong experience with Kubernetes (AKS/EKS)
Programming skills in Go or Python
Experience with cloud platforms (Azure/AWS) and on-prem systems (Linux, networking)
Platform & DevOps
Experience with CI/CD and GitOps (Flux, ArgoCD, GitHub Actions, Terraform etc)
Strong knowledge of
Observability (metrics, logs, traces)
SRE practices (SLOs, SLIs, incident management)
AI & Modern Engineering
Exposure to AI/ML or AIOps in operations
Ability to use AI tools for
Troubleshooting and automation
Improving engineering productivity
Data-driven mindset with telemetry and metrics
Good to Have
Experience in Kafka Streams, Apache Flink, MQ
Hybrid architecture experience (cloud + on-prem integration)
Troubleshooting across
Network (DNS, routing, load balancers)
Storage and disk performance
Exposure to FinOps, security, and compliance
What You’ll Get
Work on a mission-critical global platform
Deep exposure to Kafka at scale and hybrid architectures
Opportunity to shape AI-driven platform operations
Strong engineering culture focused on
Automation-first mindset
Blameless postmortems
Continuous improvement
Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.
