Senior Solutions Architect, AI Security

Cloudsine; Singapore; On-site; SGD 180,000 - 260,000; Full time

Benefits offered by this job

Equity participation

Base + variable compensation

Travel to customer sites

Job summary

CloudsineAI is seeking a senior technical owner to lead end-to-end engagements, from discovery to live production systems, on our most strategic deals in Asia. You will work with product and engineering to shape deployments for government, defence and financial services buyers.

Based in Singapore, you will travel to customer sites and influence secure architecture and runbooks. Strong experience with agentic AI, Kubernetes/OpenShift, and security design is essential.

Qualifications

• 5+ years in security engineering or architecture roles.
• Experience deploying into production across on-prem, cloud, and air-gapped environments.
• Strong English writing for scoping docs and readouts.

Responsibilities

• Lead discovery with security teams to surface constraints early.
• Design deployment across SaaS, VPC, private cloud, and on-prem environments.
• Write proposals, RFPs and tender responses.
• Execute end-to-end proofs of concept with defined success criteria.
• Define evaluation scope and run adversarial testing.
• Own deployment runbooks and reference architectures.
• Feed field requirements back to product and engineering.

Skills

LLM/agentic systems

Security engineering

Security architecture

Pre-sales engineering

Kubernetes/OpenShift

Identity and SSO integration

Strong English writing

Education

Bachelor's in CS/Security or related

Tools

Kubernetes

OpenShift

SIEM

WAF

Job description

Responsibilities

• Technical discovery and solution design: Run discovery with security architects, platform teams and CISOs to surface the real constraints early, including data residency, egress rules, model hosting, identity, and the SIEM or SOC tooling already in place.
• Design the deployment across SaaS, customer VPC, private cloud, on-premise virtual machines, Kubernetes and OpenShift, and air-gapped environments.
• Turn constraints into scoped solution options, and write the technical sections of proposals, RFP and tender responses.
• Evaluations and proofs of concept: Take proof-of-concept and pilot engagements end to end: scope, success criteria, environment build, execution, and the readout that decides the deal.
• Set what gets measured and what sits outside scope, so the evaluation tests what our product is responsible for.
• Run competitive bake-offs, including adversarial and red-team testing against LLM and agentic applications.
• Answer the hard questions with evidence: false positives, latency, integration effort and sovereignty all come up.
• Deployment: Own the technical relationship through go-live and early operation, including environment build, integration with identity and logging, guardrail and policy configuration, tuning against live traffic, and handover to the customer’s operations team.
• Set the pattern: write the deployment runbook, reference architecture and acceptance-test approach that the next engagement runs on.
• The product feedback loop: Carry field requirements back to product and engineering, a standing input to the roadmap.

Qualifications

Must-haves

• Multiple LLM or agentic systems personally built, deployed, integrated or secured, running in production, with the security thinking attached: guardrails, identity, tool access, secrets, sandboxing, evaluation.
• Systems taken all the way into production, and stayed with afterwards. Deploying into someone else’s environment teaches things that designing for it does not.
• Typically five or more years across security engineering, security architecture, solutions architecture, pre-sales engineering or technical consulting, in enterprise or public-sector environments. Less time but deeper agentic AI work is welcome.
• Breadth across deployment models, hands-on with containerised platforms, ideally Kubernetes or OpenShift, plus identity and SSO integration and network segmentation. On-premise or air-gapped experience is a strong advantage.
• A working security foundation: common attack classes, application security, and how a security team operates day to day.
• The ability to lead a technical room and set the direction of the conversation.
• Clear written English. Much of this role is scoping documents, runbooks and evaluation readouts that a procurement officer or an operations engineer reads without the author in the room.

Nice-to-haves

• Selling into or delivering for Singapore government or financial services, and familiarity with those procurement and accreditation cycles.
• AI security frameworks: OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, or MAS guidance on AI risk.
• Web security, WAF, or website monitoring and defacement protection.
• Security certifications such as CISSP, OSCP, CKA/CKAD or cloud security specialisations.

Why CloudsineAI?

At CloudsineAI, you’ll:

• Be the senior technical owner of a TraceCtrl engagement end to end, from the first discovery call to a live production system, on our highest-value deals.
• Get direct access to the people who build the product: field input here changes what gets built, in a small team with a short decision chain.
• Work on deals won in the technical room, for government, defence and financial-services buyers who depend on what you deploy.
• Gain the reach of a V-Key company, with standing in regulated institutions across Asia, without losing the speed of a founder-led company that still decides quickly.
• Be based in Singapore with regular time on customer sites, on a base-plus-variable package with equity participation set against the depth you bring.