Senior Presales Solutions Engineer

About the role We are looking for a hands‑on Senior Presales SolutionsEngineer to help enterprise customers design and validate cloud and observability solutions. Based in Singapore, you will work with sales, customers, partners and technical teams across discovery, solution design, demonstrations, proofs of concept, technical enablement and customer adoption. You will translate business and operational problems into practical architectures, working technical evidence and clear recommendations. You should use AI effectively to accelerate research, engineering and communication, while applying your own judgment to verify accuracy, protect customer information and take ownership of the result. Key responsibilities • Lead customer discovery and architecture workshops to understand applications, infrastructure, operational pain points, business objectives and constraints. Identify technical fit, gaps and the next decision required. • Design cloud, hybrid and cloud-native observability architectures covering telemetry collection, integrations, deployment, access, security, data residency, resilience and scale. Explain options and trade‑offs clearly. • Build and deliver tailored demonstrations and proofs of concept or value. Agree scope, baselines, measurable success criteria, responsibilities, resource needs and decision gates with the customer. • Provide hands‑on setup, integration, testing and troubleshooting for evaluations and agreed implementation activities. Configure collectors, instrumentation, APIs, dashboards, queries, alerts and workflows; develop scripts or lightweight integrations as needed. • Investigate application and infrastructure issues using metrics, logs and distributed traces. Demonstrate how telemetry connects a customer symptom to the affected service and underlying infrastructure, and explain the limits of the evidence. • Prepare architecture diagrams, solution briefs, presentations, technical proposals and responses to RFPs, RFIs and security questionnaires. Keep customer requirements, assumptions, evidence and product limitations explicit. • Support sizing, consumption estimates, pricing inputs and total cost of ownership comparisons. Validate units and assumptions, explain migration and parallel‑running costs, and revise recommendations when requirements change. • Use approved AI assistants and coding tools to accelerate research, scripting, analysis, documentation and demo preparation. Check outputs against reliable sources and working systems, correct errors and retain human accountability. • Partner with sales on technical qualification and account planning. Coordinate with product, engineering, support and delivery teams on blockers, feedback and handover. Support onboarding and adoption reviews, with clear delivery owners, scope and acceptance criteria. • Plan and deliver technical enablement for customers, partners and internal teams. Develop training presentations, hands‑on labs, walkthroughs and guides; adapt sessions to the audience and check understanding through practical exercises. • Maintain reusable demo assets, runbooks and learning materials. Support webinars, technical events and knowledge sharing; stay current with cloud, observability and AI developments and pursue agreed certifications. Required experience and skills • 5+ years of relevant experience in presales, solutions engineering, technical consulting, cloud engineering, DevOps, SRE, systems integration or enterprise software engineering, including direct work with enterprise customers. • Ability to independently lead technical discovery, architecture discussions and demonstrations, and to guide a bounded customer evaluation through to a clear recommendation and delivery handover. • Hands‑on experience with at least one major cloud platform, such as AWS, Microsoft Azure, Google Cloud, Alibaba Cloud, Tencent Cloud or Huawei Cloud. Understand compute, networking, identity and access management, storage, availability and cost trade‑offs. • Working knowledge of Linux, HTTP and APIs, application architectures, databases, containers and Kubernetes, with the ability to deploy, inspect and troubleshoot a small cloud‑native environment. • Practical experience with observability or monitoring, including metrics, logs, application performance monitoring and distributed tracing. Able to configure useful dashboards and alerts, investigate failures and explain findings. • Ability to read, write, debug and explain scripts or code in at least one relevant language, such as Python, JavaScript,Shell, Go or Java, and work with APIs, JSON, YAML and Git. • Demonstrated use of AI assistants or coding tools for technical work. Able to break down a task, provide useful context, assess output quality, test important claims and independently explain or reproduce the underlying reasoning. • Sound judgment in handling credentials, customer data and access permissions, including when using AI tools. Understand safe ch #J-18808-Ljbffr