Lead Development Engineer (Gen AI)

As a Lead Software Development Engineer, you will lead the design, development, and optimisation of complex software applications. You will work cross-functionally with developers in domains that span the entire travel ribbon to architect and implement scalable cloud-based solutions on AWS. This role offers an excellent opportunity for seasoned professionals to leverage their extensive experience, drive innovation, and make significant contributions to high-impact projects in a fast-paced and cutting-edge environment.
Responsibilities:
Design, develop, and maintain scalable cloud-based applications using AWS services.
Collaborate with cross-functional teams to define, design, and ship new features.
Drive a consistent experience between Delta-only and mixed metal itineraries through understanding the end-to-end ecosystem and nuances of Alliances partner travel.
Forge a new way of working through building trust, collaboration and quality of development that seamlessly integrates with other pipeline deliverables.
Build a deep and broad understanding of interdependencies between internal and external systems to architect efficient and scalable solutions.
Must be able to conduct root cause analysis to generate creative solutions enabling velocity of delivery.
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.
Mentor and guide junior engineers, fostering a culture of continuous improvement.
Stay up to date with the latest AWS technologies and industry trends.
Requirements:
7-12 years of experience in software development, with a focus on cloud technologies.
Proficiency in AWS services such as EC2 S3 Lambda, RDS, and CloudFormation.
Strong programming skills in languages such as Python, Java, or Node.js .
Experienced in deploying and managing applications using Red Hat OpenShift Service on AWS (ROSA), leveraging its robust platform for scalable and efficient cloud solutions.
Experience with containerization technologies like Docker and Kubernetes.
Familiarity with DevOps practices and tools.
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.
Understanding of prompt engineering, AI workflows, or model integration patterns.
Experience working with generative AI or LLM-based solutions is highly desirable.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.
Execute with a Sense of Urgency.
Consistently prioritises safety and security of self, others, and personal data.
Embraces diverse people, thinking, and styles.
Possesses a high school diploma, GED, or high school equivalency.
Is at least 18 years of age and has authorisation to work in the United States.
Good to Have:
Bachelor's Degree in Computer Science, Information Systems or related technical field is preferred.
Experience working in an airline technology environment is preferred.
Strong analytical, problem-solving, and communication skills to break down complex problems into concise impact statements.
AWS Certified Solutions Architect or Developer certification.
Experience with a modern front-end framework is a plus.
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.

Experience
7-11 yrs