Ensign is hiring !
Key Responsibilities
- Own the design, development, maintenance, and evolution of the in-house AIOps / ML / LLM platform, including related cloud and on-premise Kubernetes solutions.
- Translate client, security, compliance, and internal requirements into practical platform designs with cross-functional teams.
- Build and operate production ML / LLM workflows, including retraining, deployment, inference serving, monitoring, rollback, and optimisation.
- Troubleshoot production issues across application, infrastructure, networking, Linux, Kubernetes, and ML serving layers.
Qualifications / Requirements
- Strong software/platform engineering fundamentals, including system design, API design, distributed systems, scalability, reliability, observability, authentication/authorization, testing, and maintainable code design.
- Practical understanding of the ML / LLM lifecycle, including data pipelines, model training/retraining, evaluation, experiment tracking, deployment, monitoring, and production feedback loops.
- Strong development experience in Python, with working proficiency in Go and C++ for reading, debugging, maintaining, and extending existing production codebases.
- Strong Linux, networking, and Kubernetes fundamentals, including production troubleshooting, service connectivity, ingress, resource limits, workload debugging, and deployment operations.
- Experience designing, deploying, and operating production platforms on AWS, Azure, GCP, or on-premise environments.
- Experience building CI/CD, automation, and MLOps / LLMOps workflows for production ML / LLM systems.
- Strong communication skills and ability to work with AI, deployment, infrastructure, and security teams.
Good to Have
- Deep experience operating Kubernetes in bare-metal, air-gapped, or restricted on-premise environments.
- Experience with MLflow, Kubeflow, vLLM, TensorRT, TGI, or similar ML / LLM platform tools.
- Exposure to TypeScript / React or Java-based services.
Skills Required
- Strong software/platform engineering fundamentals including system and API design, distributed systems, scalability, reliability, observability, authentication/authorization, testing, and maintainable code
- Practical understanding of the ML/LLM lifecycle: data pipelines, training/retraining, evaluation, experiment tracking, deployment, monitoring, and production feedback loops
- Strong development experience in Python
- Working proficiency in Go and C++ to read, debug, maintain, and extend existing production codebases
- Strong Linux, networking, and Kubernetes fundamentals, including production troubleshooting, service connectivity, ingress, resource limits, workload debugging, and deployment operations
- Experience designing, deploying, and operating production platforms on AWS, Azure, GCP, or on-premise environments
- Experience building CI/CD, automation, and MLOps/LLMOps workflows for production ML/LLM systems
- Ability to build and operate production ML/LLM workflows including retraining, deployment, inference serving, monitoring, rollback, and optimization
- Troubleshoot production issues across application, infrastructure, networking, Linux, Kubernetes, and ML serving layers
- Strong communication skills and ability to work with AI, deployment, infrastructure, and security teams
- Deep experience operating Kubernetes in bare-metal, air-gapped, or restricted on-premise environments
- Experience with MLflow, Kubeflow, vLLM, TensorRT, TGI, or similar ML/LLM platform tools
- Exposure to TypeScript/React or Java-based services
What We Do
Ensign InfoSecurity is the largest pure-play end-to-end cybersecurity service provider in Asia. Headquartered in Singapore, Ensign offers bespoke solutions and services to address their clients’ cybersecurity needs. Their core competencies are in the provision of cybersecurity advisory and assurance services, architecture design and systems integration services, and managed security services for advanced threat detection, threat hunting, and incident response. Underpinning these competencies is in-house research and development in cybersecurity. Ensign has two decades of proven track record as a trusted and relevant service provider, serving clients from the public and private sectors in the Asia Pacific region
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