DevOps Engineer

About Hytech

Hytech is a prominent management consulting company headquartered in Australia and Singapore, with expertise in digital transformation for fintech and financial service sectors. It offers comprehensive consulting and robust middle- and back-office solutions, empowering clients to improve operations and maintain a competitive advantage in an evolving digital environment. Its clientele includes leading global trading platforms and cryptocurrency exchanges. With a workforce exceeding 2,000 professionals worldwide, Hytech operates offices across several countries including Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus, and Dubai.

Role Overview

We are looking to hire a DevOps Engineer to design, build, and manage our AWS infrastructure, Kubernetes clusters, and deployment pipelines. This position will work closely with engineering teams to enhance the speed of software delivery, bolster system reliability, and streamline operation processes for high-performing financial software systems. A significant component of this role involves leveraging AI-assisted engineering to automate repetitive tasks and achieve measurable workflow improvements.

Key Responsibilities

• Design and upkeep AWS infrastructure components including VPC, EKS, EC2, load balancers, storage solutions, and IAM configurations.
• Manage infrastructure lifecycle as code with Terraform for reproducible and auditable provisioning and changes.
• Operate Kubernetes environments, maintain Helm charts, handle autoscaling, and manage resource configurations.
• Create and enhance continuous integration and delivery (CI/CD) pipelines and GitOps processes using tools like Argo CD.
• Implement monitoring systems, logging, distributed tracing, and set up actionable alerts to improve incident management.
• Handle production incident responses, conduct root cause analysis, update runbooks, and verify backup and disaster recovery plans.
• Enhance security of infrastructure via least privilege principles, network segmentation, secrets management, vulnerability assessments, and patching.
• Partner with developers to troubleshoot deployment and performance challenges.
• Leverage AI-powered coding assistants and agent tools to speed up infrastructure coding, pipeline optimization, problem resolution, and documentation.
• Automate routine tasks using AI combined with scripting and internal tooling to develop self-service systems.
• Review and validate AI-generated code, configurations, and recommendations with proper testing and rollback strategies.
• Track performance gains demonstrating reduced deployment time, minimized manual activities, and accelerated incident diagnostics; disseminate effective methods team-wide.

Essential Qualifications

• Minimum 3 years' experience in DevOps, Site Reliability Engineering, or cloud infrastructure with operational production exposure.
• Deep expertise with AWS services alongside advanced troubleshooting skills in networking, compute resources, storage, and access control.
• Strong foundational understanding of Linux OS internals, TCP/IP networking, DNS, TLS, and load balancing methods.
• Hands-on proficiency with Docker containerization, Kubernetes orchestration, and Helm package management covering scheduling, resource limits, checks, storage, and upgrades.
• Practical skills in Terraform usage including module reusability, state handling, and executing safe infrastructure modifications.
• Experience creating and maintaining CI/CD workflows using platforms such as GitLab CI or GitHub Actions, incorporating GitOps principles.
• Familiarity with observability tooling like Prometheus, Grafana, OpenTelemetry or similar.
• Ability to script dependable automation using Python, Go, or Shell scripting languages.
• Regular practical experience with AI engineering assistants, such as Claude Code, Codex, or GitHub Copilot to enhance engineering tasks.
• Capability to present verified examples of AI-enabled workflow enhancements explaining original processes, solution deployment, validations, and outcomes.
• Sound judgment for evaluating AI outputs and managing secure production access and sensitive operational changes.
• Strong communication, comprehensive documentation abilities, and problem-solving aptitude with a commitment to follow-through on resolving incidents.

Desirable Skills

• Background in financial trading systems, real-time data platforms, or other mission-critical high-availability environments.
• Experience with Argo CD and managing multi-cluster, multi-account, or multi-region cloud setups.
• Hands-on work with Kafka, Redis/Valkey, PostgreSQL, or ClickHouse in production environments.
• Knowledge of service level indicators/objectives (SLI/SLO), capacity management, load testing, and disaster recovery planning.
• Exposure to cloud security incident handling, access governance, or compliance audits.
• Experience deploying and troubleshooting .NET applications.
• Competence in developing AI-powered internal tools or automating engineering workflows.