Software Development Engineer - Onboard Services

We are seeking a forward-looking Software Development Engineer to design, build, and scale next-generation applications leveraging cloud-native architectures, AI/ML capabilities, and modern engineering practices. As part of the Onboard Services (OBS) technology organisation, this role will help build and enhance full-stack applications that power the in-flight catering experience for millions of customers. This role supports critical systems within the Delta Onboard Service domain, ensuring reliability, scalability, and innovation across cloud-native and enterprise platforms.

Responsibilities:

• Design, develop, and maintain scalable cloud-based applications using AWS services.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Implement best practices for cloud architecture, security, and performance.
• Automate deployment, monitoring, and management of cloud applications.
• Write clean, efficient, and maintainable code and contribute to both front-end and back-end development as a full-stack engineer.
• Build and integrate AI/ML-powered features and agents into applications using AWS AI services.
• Apply AI-assisted development tools to accelerate software delivery, automate repetitive tasks, and improve code quality.
• Troubleshoot and resolve issues related to cloud infrastructure and applications.
• Stay up-to-date with the latest AWS technologies and industry trends.

Requirements:

• 2+ years of hands-on experience in full-stack software development.
• Strong proficiency in Java, J2EE, Spring Framework, and RESTful service development.
• Experience with AWS Cloud Services (EC2 S3 Lambda, API Gateway, CloudWatch, etc. ).
• Solid understanding of SQL, PL/SQL, and experience working with Oracle RDBMS.
• Front-end development experience using AngularJS, HTML, JavaScript, and CSS.
• Practical experience with GitLab, version control workflows, and GitLab CI/CD pipelines.
• Familiarity with DevOps concepts, automation, and containerization fundamentals.
• Ability to work in an Agile environment and collaborate effectively with distributed teams.
• Strong problem-solving skills, attention to detail, and a commitment to delivering high-quality software.
• Knowledge of CI/CD pipelines and tools like Jenkins, GitLab, or AWS CodePipeline.
• Hands-on experience with AWS cloud services and building distributed systems.
• Experience integrating AI/ML capabilities into applications (e. g., personalisation, NLP, recommendations).
• Familiarity with AWS AI/ML services such as Amazon SageMaker, Bedrock, and AgentCore.
• Demonstrated experience using AI-assisted development tools (e. g., GitHub Copilot, Claude, Kiro) to accomplish tasks such as generating and reviewing code, writing and maintaining tests, creating documentation, and debugging, with the judgment to validate and own AI-generated output.
• Ability to connect with peers, business analysts, and domain experts and the ability to listen to customers and colleagues; convey ideas effectively; prepare written documentation.
• Proactive in nature with a customer-centric focus, demonstrating ownership and initiative.
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts clearly.
• Consistently prioritises safety and security of self, others, and personal data.

Good to Have:

• Experience building cloud-native microservices or serverless applications on AWS.
• Knowledge of modern JavaScript frameworks beyond AngularJS (e. g., Angular, React, Vue).
• Exposure to airline, travel, or large-scale operational technology domains.
• Experience with performance tuning of Java applications and SQL queries.
• Familiarity with infrastructure-as-code tools (Terraform, CloudFormation) or container platforms (Docker, Kubernetes).
• Understanding of event-driven architectures, messaging systems, or streaming platforms.
• Strong communication skills and the ability to influence technical decisions across teams.
• Passion for improving onboard customer experience through technology.
• Experience with microservices architecture and serverless computing.
• Understanding of networking and security principles in cloud environments.
• Familiarity with Model Context Protocol (MCP) for connecting AI models to external tools and data sources.