Software Engineer

Job Summary

Platform Engineer - Event Streaming (Kafka | Cloud Hybrid)

Are you passionate about building and operating large-scale distributed systems powering real-time data? Do you enjoy combining platform engineering, automation, and AI-driven operations to deliver highly reliable and scalable systems?

Join Maersk's Technical Services Engineering as a Platform Engineer for the Event Streaming Platform, where you will help evolve a cloud-native, Kafka-based platform that enables real-time integration across global logistics systems.

This role provides a unique opportunity to work at the intersection of event streaming, cloud platforms, platform engineering, and AI-driven operations, contributing directly to Maersk's ambition of becoming a digital leader in global trade.

About the Role

We are hiring a Platform Engineer to build and operate our enterprise-scale Event Streaming Platform, a Kafka-based backbone powering real-time data across global systems.

You will work on a modern platform spanning Azure (AKS), AWS (EKS), and on-premises Kafka clusters, combining distributed systems, cloud-native engineering, and AI-driven operations.

This role is ideal for engineers passionate about Kafka at scale, platform engineering, and operational excellence.

What You'll Do Build Evolve the Platform

• Implement and enhance a scalable, multi-tenant Kafka platform across cloud and on-prem environments
• Build self-service capabilities (APIs, automation, onboarding workflows)
• 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