DevOps Engineer

Hytech; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Hytech in Singapore seeks a DevOps Engineer to build and maintain AWS infrastructure and Kubernetes platforms for high-performance financial systems. You will optimize delivery pipelines, implement GitOps, and drive AI-assisted engineering across the stack.

You will collaborate with engineering teams to improve reliability, security, and efficiency, using Terraform, Argo CD, Helm, and observability tools. The role emphasizes automation, testing, rollback procedures, and measurable improvements

Qualifications

• 3+ years in DevOps, SRE, or cloud infrastructure with production ops experience.
• Strong knowledge of AWS services and troubleshooting networking, compute, storage, and access control.
• Hands-on with Docker, Kubernetes, and Helm, including scheduling, resource management, health checks, storage, and upgrades.
• Terraform experience with reusable modules, state management, and safe changes.
• Experience building CI/CD pipelines with GitLab CI or GitHub Actions and GitOps.
• Familiarity with Prometheus, Grafana, OpenTelemetry, or equivalent observability tools.
• Ability to automate using Python, Go, or Shell.
• Regular use of AI coding assistants and agent tools in engineering workflows.
• Strong communication, documentation, and problem-solving skills.

Responsibilities

• Build and maintain AWS infrastructure (VPC, EKS, EC2, IAM).
• Manage infrastructure as code with Terraform for reproducible environments.
• Operate Kubernetes clusters, Helm charts, autoscaling, and config management.
• Develop and improve CI/CD pipelines and GitOps with Argo CD.
• Implement monitoring, logging, tracing, and alerts for reliability.
• Participate in incident response, root-cause analysis, and runbooks.
• Strengthen infrastructure security via least privilege, secrets, and patching.
• Collaborate with developers to resolve deployment and performance issues.
• Use AI coding assistants to accelerate infra development and docs.
• Automate recurring tasks and build self-service capabilities.
• Validate AI-generated code and rollback procedures.
• Measure improvements via faster delivery cycles and fewer manual steps.

Skills

AWS

Kubernetes

Docker

Terraform

CI/CD

GitOps

Python

Go

Shell

Monitoring

Tools

Argo CD

GitLab CI

GitHub Actions

Helm

Prometheus

Grafana

OpenTelemetry

Claude Code

GitHub Copilot

Job description

About Hytech

• Hytech is a leading management consulting firm headquartered in Australia and Singapore, specializing in digital transformation for fintech and financial services organizations.
• The company delivers end-to-end consulting services and provides robust middle- and back-office solutions, enabling clients to optimize operations, enhance efficiency, and stay ahead in a fast-evolving digital landscape.
• Hytech’s client portfolio includes top global trading platforms and leading crypto exchanges.
• With more than 2,000 professionals worldwide, Hytech has a strong and growing international presence, with offices across Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus, Dubai, and beyond.

About The Role

We are seeking a DevOps Engineer to build and maintain our AWS infrastructure, Kubernetes platform, and software delivery pipelines. You will collaborate closely with engineering teams to improve delivery speed, system reliability, and operational efficiency for high-performance financial systems.

AI-assisted engineering is a core aspect of this role. You are expected to actively use AI tools, automate repetitive tasks, and demonstrate measurable improvements in workflows.

Responsibilities

• Build and maintain AWS infrastructure, including VPC, EKS, EC2, load balancing, storage, and IAM.
• Manage infrastructure as code using Terraform, ensuring environment provisioning and changes are reproducible and traceable.
• Operate Kubernetes clusters and maintain Helm charts, resource configuration, autoscaling, and configuration management.
• Develop and improve CI/CD pipelines and GitOps workflows using tools such as Argo CD.
• Implement monitoring, logging, tracing, and actionable alerts to enhance incident detection and diagnosis.
• Participate in production incident response, root cause analysis, and corrective actions. Maintain runbooks and validate backup and disaster recovery procedures.
• Strengthen infrastructure security through least-privilege access, network isolation, secrets management, vulnerability scanning, and patching.
• Collaborate with developers to resolve deployment, capacity, performance, and environment issues.
• Use AI coding assistants and agent tools to accelerate infrastructure development, pipeline optimization, troubleshooting, and documentation.
• Combine AI with scripts and internal tools to automate recurring tasks and build self-service capabilities.
• Validate AI-generated code, configurations, and operational recommendations before use, with appropriate testing and rollback procedures.
• Measure improvements through shorter delivery cycles, fewer manual steps, and faster incident diagnosis, and share effective practices across the team.

Requirements

• At least 3 years of experience in DevOps, SRE, or cloud infrastructure, including hands‑on production operations.
• Strong knowledge of AWS services and the ability to troubleshoot networking, compute, storage, and access control issues.
• Solid understanding of Linux, TCP/IP, DNS, TLS, and load balancing.
• Hands‑on experience with Docker, Kubernetes, and Helm, including scheduling, resource management, health checks, storage, and cluster upgrades.
• Practical experience with Terraform, including reusable modules, state management, and safe infrastructure changes.
• Experience building and maintaining CI/CD pipelines, with familiarity with platforms such as GitLab CI or GitHub Actions and an understanding of GitOps.
• Familiarity with Prometheus, Grafana, OpenTelemetry, or equivalent observability tools.
• Ability to build reliable automation using Python, Go, or Shell.
• Regular use of AI coding assistants or agent tools, such as Claude Code, Codex, GitHub Copilot, or equivalents, in engineering workflows.
• Ability to provide concrete examples of AI‑driven efficiency improvements, explaining the original workflow, implementation, validation, and results.
• Sound judgment when reviewing AI output and handling production access, sensitive information, and operational changes.
• Strong communication, documentation, and problem‑solving skills, with ownership of issues through resolution.

Nice to Have

• Experience with financial trading, real‑time data platforms, or other high‑availability systems.
• Experience with Argo CD and multi‑cluster, multi‑account, or multi‑region infrastructure.
• Production experience with Kafka, Redis/Valkey, PostgreSQL, or ClickHouse.
• Familiarity with SLI/SLO practices, capacity planning, load testing, and disaster recovery.
• Experience with cloud security incident response, access governance, or compliance audits.
• Experience deploying and diagnosing .NET applications.
• Experience building AI‑assisted internal tools or automated engineering workflows.