Solutions Engineer

You will own the technical journey from customer discovery and enterprise setup through successful operation. The work spans public AI configuration, Internal AI connections, identity, data boundaries, observability, support and the technical evidence needed for security review.

This is a delivery and operations role spanning technical discovery, implementation, onboarding and ongoing support—not a demo-only position. You will make each setup operable, examinable and supportable after go-live while helping Lawnise run reliably day to day.

Lawnise verifies both public AI and the AI an enterprise deploys. Each scope creates different setup and operating demands: public AI work requires dependable project, prompt and scan configuration, while Internal AI validation must also respect enterprise identity, data, network and authorisation constraints. This role makes both paths repeatable and reliable.

• Run technical discovery and configure the customer's organisation, projects, access, prompts, knowledge sources and approved verification scope.
• Set up and monitor public AI scans, engine configuration and delivery workflows with the assurance team.
• Build and maintain approved API, event, log and AI-platform connectors, including supported enterprise SSO and Internal AI authentication methods.
• Define data-flow, access, tenancy and failure boundaries with platform and customer security teams.
• Lead the technical parts of security, architecture and technology-risk reviews with evidence from the implemented design.
• Build deployment, support, rollback and incident runbooks, and establish observability and operational ownership before service commitments begin.
• Support day-to-day Lawnise operations, including failed scans, connector issues, customer technical requests, delivery dependencies and production triage.
• Diagnose failures across Lawnise, customer infrastructure and third-party AI platforms without blurring accountability.
• Turn one-off integration lessons into reusable product capabilities and implementation standards.

• Significant experience in software, platform, solutions or customer engineering for enterprise systems.
• Strong implementation ability in Python or TypeScript and practical SQL/PostgreSQL experience.
• Cloud-operating experience involving identity, secrets, networking, deployment and observability; GCP experience is useful, equivalent depth elsewhere is valid.
• Delivery of SaaS or platform integrations into enterprise identity, network and security environments.
• The ability to explain an architecture to engineers, security reviewers and non-engineering owners without changing the facts for each audience.
• Experience owning production readiness, incident response or operational handover.

Experience in financial services or another regulated industry is valuable. Familiarity with enterprise AI platforms, model gateways, agent or MCP integrations, enterprise SSO and audit logging will shorten the learning curve. Bahasa Malaysia is useful for the launch market.

We are open to a full-time or fractional arrangement, depending on experience, availability and the operating coverage agreed together. The role is broader than a single integration project and includes both customer delivery and ongoing Lawnise technical operations.

Operational responsibility, support hours and any production on-call expectations will be agreed explicitly; on-call does not arise by implication.

The final arrangement, responsibilities and decision authority will be confirmed in writing before the engagement begins.