Job Purpose/summary

As an AI Engineer – SRE & Service Excellence, you will build intelligent, automated, and resilient engineering solutions across SbM-supported services.

This is a hands-on engineering role combining Java/Python development, GenAI, automation, observability, and SRE practices. You will analyse complex technical problems, improve service reliability and recovery, build AI-powered operational capabilities, and reduce recurring disruptions through proactive engineering and automation.

The focus is not just on fixing problems, but on understanding them, preventing recurrence, automating repetitive work, and using AI/GenAI to build smarter operational solutions across warehouses, offices, and GSC environments.

Key responsibilities

- Design and develop engineering solutions using Java and/or Python.
- Build and implement AI/GenAI-powered solutions for troubleshooting, root-cause analysis, knowledge discovery, operational intelligence, and automation.
- Apply SRE and reliability engineering practices to improve service availability, resilience, recovery, and operational efficiency.
- Build early-warning and real-time visibility using observability platforms, monitoring data, logs, metrics, traces, and telemetry.
- Develop dashboards, alert thresholds, service health indicators, and recovery metrics for critical services and infrastructure.
- Analyse complex technical problems across applications, cloud platforms, infrastructure, networks, and distributed systems.
- Conduct structured Root Cause Analysis (RCA) and drive permanent corrective and preventive actions.
- Identify recurring failure patterns, technical debt, systemic weaknesses, and operational gaps.
- Implement automation-driven remediation and recovery workflows to reduce manual effort and operational toil.
- Explore and implement AI-assisted troubleshooting, decision support, and self-healing capabilities where appropriate.
- Reduce false alarms, repeated disruptions, and reactive firefighting through proactive engineering practices.
- Maintain and prioritise a reliability and improvement backlog focused on prevention, automation, and operational resilience.
- Create and maintain runbooks, playbooks, troubleshooting guides, and standard response workflows.
- Collaborate with Application, Platform, Cloud, Infrastructure, and Network teams to improve reliability and operational readiness.
- Champion proactive engineering, observability, automation,



and AI-driven operational practices across teams and regions.

Tech skills

- Strong hands-on programming skills in Java and/or Python.
- Experience with Generative AI, LLMs, AI APIs, AI-assisted automation, RAG, AI agents, or similar technologies.
- Experience building APIs, integrations, automation tools, or backend services.
- Understanding of SRE principles, including reliability, observability, automation, recovery, and reduction of operational toil.
- Experience with monitoring and observability platforms, including logs, metrics, traces, telemetry, dashboards, and alerting.
- Hands-on exposure to cloud platforms such as Azure, AWS, or equivalent.
- Knowledge of distributed systems, microservices, enterprise applications, infrastructure, or networking.
- Experience with automation using scripts, APIs, workflows, or orchestration tools.
- Familiarity with CI/CD, containers, and cloud-native technologies is an advantage.
- Understanding of root-cause analysis, problem prevention, and reliability engineering practices.

Required experience

- 3–8 years of experience in Software Engineering, AI Engineering, SRE, Platform Engineering, DevOps, Infrastructure Engineering, or Technical Operations.
- Strong hands-on experience developing solutions using Java and/or Python.
- Experience or strong practical exposure to GenAI, LLMs, AI-powered automation, or AI-assisted engineering tools.
- Experience working with monitoring systems, observability platforms, dashboards, telemetry, logs, metrics, and event data.
- Demonstrated ability to analyse and solve complex technical problems in enterprise or distributed environments.
- Experience automating repetitive tasks and building scalable engineering solutions.
- Hands-on exposure to cloud platforms, infrastructure, enterprise applications, or distributed systems.
- Experience with technical troubleshooting, root-cause analysis, service recovery, and operational improvement is preferred.
- Experience working across distributed or multi-region environments is an advantage.

Qualifications

- Bachelor’s degree in Computer Science,



Engineering, IT, or a related technical field.
- Certifications or practical experience in Cloud, AI/ML, GenAI, SRE, DevOps, or Infrastructure Engineering are beneficial.
- Strong analytical and diagnostic capabilities with structured problem-solving skills.
- Familiarity with modern software engineering, cloud, automation, and observability practices.
- Demonstrated curiosity and willingness to explore and apply emerging AI and GenAI technologies to real-world engineering challenges.

Business skills

- Excellent problem-solving and analytical skills.
- Strong ownership and motivation to solve problems at their root rather than applying temporary fixes.
- Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
- Ability to collaborate effectively with Application, Platform, Cloud, Infrastructure, and Network teams.
- Ability to work independently while contributing effectively to cross-functional and global teams.
- Proactive mindset with a strong focus on prevention, automation, and continuous improvement.
- Ability to manage multiple priorities and work effectively in a energetic environment.
- Strong attention to detail while maintaining a big-picture view of system reliability and business impact.
- Ability to influence others and drive adoption of better engineering, automation, observability, and operational practices.
- A results-oriented and action-driven mindset with a strong sense of ownership and urgency.
- Curiosity and enthusiasm for combining Software Engineering + SRE + Automation + GenAI to build smarter and more resilient services.

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 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 [email protected].

📌 Service Excellence Engineer (India)
🏢 A.P. Moller - Maersk
📍 India