Software DevOps Engineer

As a Senior Software DevOps Engineer, you will build our digital product and services that power our Airline customers and continuously improve our engineering practices. You will design, implement and deploy applications and backend business services that will empower passenger experience for our Airline customers and build data analytical solutions for better monitoring and reporting capabilities for our operational support teams. You will be an individual contributor in a high visibility role, positioning you to deliver high impact at Thales Inflyt Experience digital engineering team and challenging you with learning opportunities that will help you grow and accelerate your career.

Essential Functions / Key Areas of Responsibility

Essential Duties and Responsibilities: DevOps Engineer, to design, develop and deploy, and take ownership for the applications and services that are owned by your team.

Responsibilities

• Take end-to-end technical ownership of complex features and subsystems, from requirements and architecture through development, testing, deployment, observability, and production support.

• Collaborate with Product Owners, Product Management, Data/AI teams, and engineering squads to translate business and operational needs into scalable technical solutions.

• Lead the technical design and architecture of cloud-native applications, ensuring scalability, performance, reliability, security, maintainability, and operational readiness.

• Design and integrate AI-enabled applications and intelligent workflows, leveraging LLMs, Agentic AI, enterprise APIs, and data platforms where they deliver measurable value.

• Apply robust engineering practices to AI-enabled solutions, including data security, access control, grounding, guardrails, evaluation, observability, performance, and responsible AI.

• Drive AI-augmented software engineering across the SDLC, using tools such as Kiro or equivalent AI-assisted development platforms for requirements/specification, design, coding, testing, code review, documentation, and troubleshooting while maintaining engineering accountability.

• Establish and champion engineering quality and automation standards across code quality, API design, automated testing, security, CI/CD, observability, documentation, and AI-assisted development.

• Take accountability for delivery and production quality, leading design/code reviews, proactively addressing architectural risks, technical debt and performance bottlenecks, and driving issues through resolution.

• Mentor and technically guide engineers while continuously evaluating emerging AI, cloud, data, and software engineering technologies and influencing technical decisions that improve engineering productivity and product outcomes.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline.

• 5-8 years of relevant software engineering experience.

• Strong programming skills in full-stack development, Core Java, and REST APIs.

• Good experience in the design, development, management, and consumption of REST APIs, including Postman and API gateways.

• Experience with microservices, containers, Kubernetes, orchestration, CI/CD, and cloud-native application development.

• Understanding of database and data engineering fundamentals hands-on experience with PostgreSQL is an added advantage.

• Experience or strong understanding of LLMs and Generative AI, including integration of LLM capabilities into enterprise applications and workflows.

• Understanding of Agentic AI architectures, including AI agents, tool/function calling, workflow orchestration, and integration with enterprise APIs and data sources.

• Experience building AI-driven data use cases, such as conversational analytics, natural-language-to-SQL, automated insights, data summarization, and intelligent decision-support workflows.

• Familiarity with RAG, embeddings, vector databases, prompt engineering, and grounding LLMs with enterprise data would be an advantage. Understanding of AI security, data privacy, access control, observability, and responsible use of LLMs in enterprise environments.

• Experience in security software/domain and Agile software development. Enjoy translating complex business, operational, data, and technical requirements into robust and scalable architectures.