HRS Group

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.