AI Cyber Solutions Engineer

SGInnovate; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

CloudsineAI is seeking a solutions engineer to own the technical room from discovery to evaluation. You will work closely with our Chief Commercial Officer and enterprise sales to win high-value TraceCtrl opportunities, while occasionally supporting other security offerings.

You will run technical discovery with security architects and CISOs, design deployment options across SaaS/private cloud/on‑premise/air-gapped environments, and write the technical sections of proposals and tenders.

Qualifications

• 5–8 years in solutions engineering, pre-sales or security architecture with enterprise buyers.
• 2–3 years hands-on with LLM or agentic systems, built/deployed/secured them.
• Fluency across deployment models: SaaS, private cloud, on‑premise, containerised and air-gapped.
• Working security foundation: common attack classes and application security.
• Ability to lead a technical room with buyers including CEO, product management and security researchers.
• Clear written English for scoping documents and evaluation readouts.
• Preferred: Experience selling into Singapore government or financial services.
• Preferred: Knowledge of AI security frameworks (OWASP Top 10 for LLM, MITRE ATLAS, NIST AI RMF) or MAS guidance.
• Preferred: Web security, WAF or website monitoring experience.
• Preferred: Security certifications (CISSP, OSCP) welcomed but not substitutes.

Responsibilities

• Own clear technical discovery of customer pain points and persuasive solution design. Surface constraints like data residency, egress, model hosting, identity, and existing SIEM/SOC tooling.
• Design deployments: SaaS, private cloud, on‑premise, containerised platforms, and air‑gapped environments; translate constraints into scoped options.
• Own demonstrations, POCs and evaluations from scope to readout and deal closure.
• Lead bake-offs and adversarial testing to address false positives, latency, integration effort, and sovereignty concerns.
• Contribute to product feedback loop with structured field requirements for roadmap.

Skills

Solutions engineering

LLM systems

Deployment models

Security fundamentals

Technical leadership

Written English

Gov/FS sales

AI security frameworks

Web security

Security certifications

Job description

This role is posted on behalf of Cloudsine, a startup supported by SGInnovate.

Background

CloudsineAI builds AI agent security and governance software. Founded in Singapore in 2012, we protect over 12,000 web properties for customers across five countries, and our platform secures LLM and agentic applications inside some of the region's most tightly regulated environments - including a large Singapore government agency running up to 100 public-facing LLM applications. We are the sovereign AI-agent security platform for regulated Asia-Pacific. TraceCtrl, our agentic AI governance platform, is where we are placing our weight. Deals like these are won or lost in the technical room: buyers in government, defence and financial services do not buy from a slide - they buy after an evaluation, run in their own environment, against their own constraints. This role owns that room, paired with enterprise sales.

Job scope

You are the technical owner of a TraceCtrl opportunity from first discovery call through to a completed evaluation. You work directly alongside the Chief Commercial Officer and our enterprise sales motion on high-value, high-touch deals.

TraceCtrl is the priority and the clear majority of this role. You will occasionally support evaluations across the rest of our portfolio - web security and monitoring - where the technical question overlaps. We are looking for Solutions Engineers who are hungry to win deals (in partnership with Sales Team).

Two things you own, and one you contribute to.

You own: clear technical discovery of customer pain points and persuasive solution design

Run discovery with security architects, platform teams and CISOs - surface the real constraints before anyone proposes anything: data residency, egress restrictions, model hosting, identity, and the SIEM or SOC tooling already in place.

Design the deployment. SaaS, customer VPC or private cloud, on-premise virtual machines, containerised platforms such as Kubernetes and OpenShift, and fully air-gapped environments where licensing, model updates and telemetry all behave differently.

Translate constraints into scoped solution options, and write the technical sections of proposals, RFP and tender responses.

You own: demonstrations, POCs and evaluations

Take proof-of-concept and pilot engagements end to end: scope, success criteria, environment build, execution, and the readout that closes or kills the deal.

Define what gets measured - and, just as importantly, what is explicitly out of scope - so an evaluation is scored on the things our product actually determines.

Run competitive bake-offs, including adversarial and red-team style testing against LLM and agentic applications.

Handle the objection you cannot deflect: false positives, latency, integration effort, sovereignty. Answer it with evidence, not assertion.

You contribute to: the product feedback loop

• Carry structured field requirements back to product and engineering - what customers actually asked for, how often, and what it cost us when we could not deliver it. This is a standing input to the roadmap, not a documentation workstream. Narrative, positioning and technical content sit with our technical product manager; you are not being hired to write them.

Throughline KPI: evaluations entered are evaluations won

Ninety-day success in this role looks like:

• A meaningful number of TraceCtrl evaluations advanced alongside enterprise sales, with you as the technical lead.
• Time from first technical conversation to evaluation sign-off measurably shorter than it is today.
• Product engineers no longer pulled into routine customer calls, because you are handling them.

Requirements

• 5-8 years in solutions engineering, pre-sales, technical consulting or security architecture - with enterprise or public-sector buyers, not SMB self-serve.
• Two to three years hands-on with LLM or agentic systems. You have built, deployed, integrated or secured them yourself. Reading about them does not count.
• Real fluency across deployment models: SaaS, private cloud, on-premise, containerised and air-gapped - including what breaks in each. Comfort with identity and SSO integration, network segmentation, and agent- or endpoint-based deployment across distributed estates.
• A working security foundation: common attack classes, application security, and how a security team actually operates day to day.
• The ability to lead a technical room. Our buyers are sceptical by profession and will aim their hardest questions at you. You set the direction of that conversation - with our CEO, product management and security research colleagues to draw in when a question genuinely needs them.
• Clear written English. A large share of this role is scoping documents and evaluation readouts that a procurement officer will read without you there to explain them.
• Preferred - Experience selling into Singapore government or financial services, and familiarity with how those procurement cycles actually run.
• Preferred - Working knowledge of AI security frameworks - OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF - or of MAS guidance on AI risk.
• Preferred - Background in web security, WAF, or website monitoring and defacement protection.
• Preferred - Security certifications (CISSP, OSCP, cloud security specialisations) are welcome but will not substitute for the application bar above.