Software Engineer - Java and Spring Boot

Team/Opportunity:

We are hiring a JL3 Software Engineer to build and run core services in the Maersk Rate Engine (MRE) ecosystem. You will work on high-scale rate flows across various upstream, master data, and downstream execution systems through Kafka events and APIs, building resilient microservices and integrations that directly impact pricing quality, speed, and downstream commercial systems.
You will also leverage AI-assisted engineering practices to accelerate delivery, improve software quality, and enhance operational efficiency. This includes practical use of tools such as GitHub Copilot, Cursor, and AI-powered development workflows, as well as leveraging AI-enabled capabilities and engineering solutions where they create measurable business and operational value.
The role combines strong backend engineering fundamentals with a modern AI-enabled software development mindset.

What You’ll Do:

• Build and own backend services in Java and Spring Boot for rate ingestion, validation, transformation, and publishing.
• Design robust integration patterns (APIs and events) between MRE and connected systems.
• Improve reliability and performance of distributed services, including latency, throughput, fault tolerance, and recovery.
• Implement observability practices through metrics, logging, tracing, and alerting, and participate in production incident response and root cause analysis.
• Contribute to secure engineering practices including authentication, authorization, secrets management, and service hardening.
• Work in modern delivery workflows using GitHub, GitHub Actions, CI/CD, code reviews, and AI-assisted engineering tools such as GitHub Copilot and Cursor to improve software quality and delivery speed.
• Collaborate with product, architecture, and platform teams on technical design and delivery.
• Design and build services that enable automation, operational insights, and data-driven decision-making across the MRE ecosystem.
• Collaborate with platform and architecture teams to evaluate and adopt emerging AI technologies, patterns, and engineering practices that improve developer experience and operational excellence.
• Contribute to observability and analytical capabilities that support predictive monitoring, anomaly detection, and operational insights.
• Own and operate production services, ensuring high availability, rapid incident resolution, and continuous operational improvement.

Must-Have Skills & Experience:

• 3–6 years of backend engineering experience (JL3 level).
• Strong coding skills in Java (11/17+) and Spring Boot microservices.
• Good understanding of distributed systems fundamentals, including concurrency, idempotency, retries, circuit breakers, and eventual consistency.
• Hands-on experience with Kafka (or equivalent messaging platforms), REST APIs, and integration-heavy services.
• Experience deploying and operating workloads on Azure, preferably AKS and related cloud services.
• Familiarity with CI/CD and Git-based engineering workflows using GitHub.
• Familiarity with AI-assisted engineering tools such as GitHub Copilot, Cursor, or equivalent platforms.
• Strong debugging skills, ownership mindset, and communication skills.

AI-Enabled Engineering

At Maersk, we view AI as a force multiplier for engineering excellence. Engineers in this role are expected to:

• Adopt AI-assisted development practices to accelerate delivery while maintaining high standards of quality, security, and reliability.
• Identify opportunities to improve developer productivity, operational efficiency, and customer outcomes through responsible use of AI technologies.
• Contribute to a culture of experimentation, automation, and data-driven decision-making.
• Apply responsible AI principles to ensure solutions remain secure, transparent, and aligned with business objectives.

Education:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline (or equivalent practical experience).

Good-to-Have:

• Experience in pricing, rates, logistics, transportation, or supply chain domains.
• Exposure to performance tuning of high-volume transactional systems.
• Experience integrating AI services, LLM APIs, or intelligent automation capabilities into enterprise applications.
• Exposure to Azure AI, OpenAI, MLOps concepts, or model-serving platforms.
• Experience using AI-assisted engineering tools in design, development, testing, and code review wor…