DevOps Engineer

Founded in 2010, ThinkMarkets is a multi-award-winning, premium CFD brokerage, backed by multiple global regulatory licences, operating across six continents - with regional hubs spanning London, Melbourne, the Middle East, Asia-Pacific, South Africa, and the Americas. We give traders and investors seamless access to a wide range of global markets; forex, equities, indices, commodities, cryptocurrencies, futures, and more, all through our proprietary, award-winning ThinkTrader platform.
We are seeking a highly skilled Senior DevOps Engineer to oversee the architecture, automation, and reliability of our global trading infrastructure. As we provide 24-hour market access, this role is critical in ensuring mission-critical systems are scalable, secure, and highly available. You will be using compound AI agentic models to spearhead productivity and to optimize workflows. You will lead the charge in driving operational excellence, implementing advanced observability, and managing the complex data pipelines that power our real-time trading solutions.
Key Responsibilities
Infrastructure & Cloud Operations:

• Design, build, and maintain scalable, secure, and highly available infrastructure across AWS and/or GCP
• Manage multi-region cloud architectures with focus on reliability, performance, and cost optimization
• Implement and manage containerized environments using Docker and Kubernetes (EKS, GKE, or OpenShift)
• Lead cloud migration initiatives and infrastructure modernization projects
• Develop and maintain Infrastructure as Code using Terraform and other automation tools
  

Observability & Monitoring:

• Design and implement comprehensive observability solutions using tools such as Elastic Stack, Prometheus, Grafana
• Build and maintain centralized logging and monitoring platforms
• Deploy and configure data ingestion pipelines and log aggregation systems
• Create dashboards and alerts for infrastructure monitoring, application performance, and error tracking
• Implement observability best practices including distributed tracing and metrics collection
  
  

CI/CD & Automation:

• Administer and optimize Kafka clusters (on-premise and managed services like AWS MSK)
• Manage data streaming applications, including setup, tuning, security (SSL/Kerberos), and performance optimization
• Support data pipeline operations including ETL processes and data warehouse integration (Redshift or similar.
  

Agentic AI:

• Experience with AI/ML model deployment and serving (e.g., KubeFlow, SageMaker, or similar)
• Experience with GPU infrastructure provisioning and management
• Familiarity with vector databases and RAG architectures
• Understanding of AI security best practices (prompt injection mitigation, data privacy, access controls)
  

Requirements

• Experience: 8+ years of experience in DevOps, CloudOps, or SRE roles, with a proven track record in production-grade Kubernetes and Terraform environments.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.

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• Expert-level Linux/Unix administration and strong scripting skills (Bash, etc.).
• AI: Comfortable working in an agentic AI-driven team.
• Deep understanding of cloud architecture, networking concepts, and security principles.
• Experience managing CI/CD pipeline in production environments.
• Extensive knowledge of Infrastructure as Code (Terraform required).
• Hands-on experience with version control (Git) and observability platforms (ELK, Datadog).
• Communication: Excellent communication skills, with the ability to present technical infrastructure strategies to senior management and work collaboratively across departments.
• Resilience: Ability to thrive in a fast-paced environment with 24/7 production support responsibilities.
  

Preferred Qualifications

• Certifications: AWS Solutions Architect/SysOps, CKA/CKAD, or Red Hat Certified Engineer (RHCE).
• Advanced Skills: Experience with multi-cloud (AWS + GCP), Kafka cluster tuning, and OpenTelemetry.
• Experience with multi-cloud or hybrid-cloud architecture
• Industry Knowledge: Familiarity with financial data analytics platforms and ETL processes.