Senior DevSecOps Engineer - Search & Book at HRS · Ho Chi…

Senior DevSecOps Engineer - Connect Search & Book

HRS As a Company

HRS is a global technology company revolutionizing the way businesses manage lodging and meetings through AI-driven, data-centric solutions. With over 50 years of innovation, HRS delivers value through its Lodging-as-a-Service (LaaS), Meeting-as-a-Service (MaaS), and Workforce-as-a-Service (WaaS) offerings, serving Fortune 500 enterprises, leading hotel chains, and small to medium-sized businesses. By integrating technology solutions across ProcureTech, TravelTech, and FinTech, HRS creates unmatched efficiencies and drives strategic outcomes for clients globally.

Business Unit

The Search & Book unit at HRS plays a pivotal role in delivering innovative solutions through HRS Connect, the company's flagship product within the expansive global corporate travel management market. HRS Connect specifically targets the rapidly growing and significantly underserved segments of corporate lodging, meetings, groups, and long stays. The unit develops, enhances, and maintains complex technology solutions that seamlessly integrate hotel distribution systems, Property Management Systems (PMS), Online Travel Agencies (OTA), and Hotel Chain systems into the HRS Connect platform. Leveraging robust connectivity, innovative technology, and data-driven insights, the unit ensures seamless connectivity, optimized travel spend, enhanced traveler experiences, and high-performance booking solutions for global enterprise customers.

Position

We are looking for a Senior DevOps Engineer who will help build, operate, and improve the cloud infrastructure and delivery platform for Connect Search & Book. This is a hands-on engineering role focused on reliable cloud operations, Kubernetes, CI/CD automation, observability, infrastructure-as-code, practical DevSecOps practices, and AI-assisted engineering workflows.

You bring 7+ years of hands-on experience across DevOps, cloud infrastructure, platform engineering, SRE, or infrastructure engineering. You have operated production systems, automated software delivery workflows, supported incident response, and improved infrastructure reliability, security, and developer experience. You are comfortable using AI and agentic AI tools to accelerate infrastructure automation, troubleshooting, documentation, and operational workflows while applying strong engineering judgment and validation.

Challenges

• Build, maintain, and improve reliable cloud infrastructure for Connect Search & Book across production and non-production environments.

• Design, operate, and optimize CI/CD pipelines to support fast, reliable, and secure software delivery.

• Manage containerized workloads using Docker, Kubernetes, Helm, and GitOps delivery practices.

• Implement and maintain Infrastructure as Code using Terraform or equivalent tools.

• Improve system observability through monitoring, logging, alerting, dashboards, and operational runbooks.

• Support production incidents, troubleshooting, root cause analysis, and post-incident improvement actions.

• Strengthen cloud security, IAM, secrets management, vulnerability scanning, and secure deployment practices.

• Improve release reliability, deployment automation, rollback processes, and environment consistency.

• Collaborate closely with software engineering teams to improve developer experience, platform usability, and operational standards.

• Apply AI and agentic AI tools to improve DevOps workflows such as CI/CD optimization, infrastructure code generation, alert triage, RCA drafting, runbook retrieval, log analysis, and operational automation.

• Validate AI-generated outputs for correctness, security, reliability, and production readiness before applying them to infrastructure or delivery workflows.

What You Bring

Experience

• 7+ years of hands-on experience in DevOps, cloud engineering, platform engineering, SRE, infrastructure engineering, or related roles.

• Proven experience operating production systems with strong requirements around availability, reliability, performance, and security.

• Experience building and maintaining CI/CD pipelines, cloud infrastructure, Kubernetes platforms, and automated operational workflows.

• Experience working in enterprise, SaaS, travel technology, fintech, e-commerce, or other high-availability production environments is preferred.

• Practical experience using AI-assisted or agentic AI tools in engineering workflows is strongly preferred.

Technical Depth - DevOps & Platform

• Strong hands-on experience with CI/CD platforms such as GitLab CI, GitHub Actions, Jenkins, CircleCI, or equivalent.

• Strong experience with container orchestration, preferably Kubernetes/EKS or equivalent, Docker, Helm, and GitOps patterns such as Argo CD or Flux.

• Infrastructure-as-Code experience with Terraform or equivalent tools, including reusable modules, environment management, code review, and state management.

• Strong Linux system administration, networking fundamentals, scripting, troubleshooting, and production operations skills.

• Experience with cloud platforms such as AWS, Azure, or GCP, with practical understanding of compute, networking, IAM, storage, logging, and managed services.

• Experience designing and operating resilient systems, including backup, restore, disaster recovery, autoscaling, high availability, and rollback strategies.

Observability & Reliability

• Hands-on experience with monitoring, logging, and alerting tools such as Prometheus, Grafana, CloudWatch, ELK/OpenSearch, Datadog, or equivalent.

• Ability to define useful alerts, dashboards, SLIs/SLOs, and operational metrics for production services.

• Experience supporting incident response, root cause analysis, and follow-up remediation.

• Understanding of delivery and reliability metrics such as lead time, deployment frequency, change failure rate, MTTR, availability, and error budgets.

• Ability to use AI-assisted analysis for log investigation, anomaly review, incident summarization, runbook lookup, and RCA drafting while maintaining human verification for production decisions.

Security & DevSecOps

• Good understanding of cloud security, IAM, least-privilege access, network security, secrets management, and secure CI/CD practices.

• Practical experience with security tooling such as secrets scanning, SAST, SCA, container image scanning, IaC scanning, or vulnerability management tools.

• Experience with secrets management using AWS Secrets Manager, HashiCorp Vault, cloud-native secret stores, or equivalent.

• Familiarity with Kubernetes security practices such as RBAC, network policies, admission controls, image scanning, and secure workload configuration.

• Awareness of software supply chain security concepts such as SBOMs, dependency governance, image signing, and private registry controls is a plus.

• Understanding of security risks introduced by AI and agentic workflows, including prompt injection through logs or tickets, over-privileged automation, unsafe command execution, data leakage, and unvalidated model output.

AI & Agentic AI Engineering Practices

• Hands-on familiarity with AI-assisted engineering tools such as GitHub Copilot, Cursor, Claude Code, OpenAI Codex, or similar tools for infrastructure, automation, debugging, and documentation workflows.

• Ability to use LLMs or agentic AI tools to generate and improve Terraform modules, Kubernetes manifests, CI/CD pipeline definitions, scripts, runbooks, dashboards, and operational documentation.

• Experience designing safe human-in-the-loop workflows where AI can propose changes, summarize incidents, or recommend remediation, but engineers validate and approve production actions.

• Ability to write clear prompts, review AI-generated code/configuration critically, test outputs, and ensure generated infrastructure changes meet security and reliability standards.

• Understanding of how to constrain agentic AI tools with least-privilege permissions, scoped credentials, sandboxed execution, audit logging, approval gates, and rollback plans.

• AI-first mindset: regularly asks whether repetitive DevOps work can be automated, accelerated, or improved using AI while preserving correctness, security, and operational control.

Automation & Engineering Practices

• Strong scripting or programming ability using Bash, Python, Go, or similar languages.

• Ability to automate repetitive operational tasks, reduce manual deployment steps, and improve platform self-service capabilities.

• Experience writing clear documentation, runbooks, operational guidelines, and reusable templates.

• Ability to evaluate trade-offs between reliability, security, cost, and delivery speed.

Collaboration & Communication

• Strong collaboration skills with software engineers, QA, product, security, and infrastructure stakeholders.

• Clear written and verbal communication skills in English.

• Ability to explain technical trade-offs, operational risks, and infrastructure recommendations clearly.

• Comfortable working in a fast-paced environment with changing priorities and production delivery expectations.

Personal Attributes

• Hands-on operator mindset: comfortable owning infrastructure issues from detection through resolution.

• Automation-first mindset: prefers repeatable, documented, automated solutions over manual operational work.

• AI-first engineering mindset: actively uses AI and agentic AI tools to improve speed and quality, while validating outputs with disciplined engineering controls.

• Reliability-focused: designs for availability, observability, recoverability, and safe change management.

• Security-aware: understands that secure delivery is part of good DevOps practice, not a separate afterthought.

• Empathy, authenticity, integrity, commitment, resilience, and respect in dealing with all stakeholders.