Senior Platform / Systems Engineer

top of pageGet a DemoSenior Platform / Systems Engineer Location: Singapore Employment Type: Full-time Work Arrangement: Hybrid / on-site, depending on project needs Compensation: Competitive base compensation, aligned with experience and role scope Work Eligibility: Applicants must have the right to work in Singapore ​ About Nestria AI Nestria AI is a Singapore-based high-assurance agentic AI startup building reliable, secure, and enterprise-ready AI systems for regulated and IP-sensitive industries. Our platform helps enterprises deploy agentic AI safely through runtime assurance, observability, verification workflows, secure orchestration, and customer-ready deployment environments. We are building a creative, collaborative, and curiosity-led culture where people are encouraged to challenge the status quo, communicate openly, move with ownership, and support each other with empathy and respect. ​ ​ About the Role We are looking for a Senior Platform / Systems Engineer to lead the development and hardening of our core runtime platform. This role is ideal for an engineer who enjoys building reliable backend systems, secure deployment workflows, scalable infrastructure, and customer-ready platform capabilities in a fast-moving startup environment. ​ As an early team member, you will work closely with the founders and have the opportunity to shape the product, engineering culture, and customer-facing platform as the company grows. ​ ​ Key Responsibilities Lead development and hardening of the core runtime platform, including gateway services, backend services, orchestration components, and integration layers. Design and improve secure deployment workflows for customer-like environments, including cloud, VPC, on-premise, and restricted network setups. Build and maintain backend architecture components that support AI agents, runtime assurance workflows, verification layers, and observability. Set up and improve CI/CD pipelines, automated testing workflows, release processes, and deployment packaging. Implement system monitoring, logging, tracing, performance metrics, and reliability tooling. Optimise platform performance, scalability, latency, and fault tolerance. Support integration with enterprise systems, APIs, databases, model providers, and internal tools. Develop secure engineering practices around authentication, secrets management, access control, networking, and environment configuration. Prepare technical documentation, deployment guides, and engineering handover materials for pilots and customer engagements. Work closely with AI engineers to ensure AI workflows can run reliably within the platform. ​ Requirements Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field. Master’s degree is preferred. Strong backend engineering experience with Python, Go, Java, Node.js, or similar languages. Experience designing and operating production-grade systems, APIs, services, and distributed applications. Strong understanding of cloud infrastructure, containers, Docker, Kubernetes, CI/CD, and DevOps practices. Experience with observability tools, logging, monitoring, tracing, and performance optimisation. Familiarity with secure deployment practices, authentication, networking, secrets management, and system hardening. Ability to work independently in a startup environment with high ownership and limited structure. Strong debugging, system design, and technical problem-solving skills. ​ Nice to Have Experience with AI platforms, LLM applications, agentic AI systems, MLOps, or model-serving infrastructure. Experience with on-premise, air-gapped, or enterprise-restricted deployment environments. Familiarity with security engineering, compliance, runtime monitoring, or enterprise governance tools. Experience building developer platforms, internal tools, or orchestration systems. ​ What We Look For Strong curiosity to learn and build in a...