Jobs at Inviso Corporation

Supports Microsoft partners across Asia by coaching them on investment programs, pipeline management, co-sell readiness, and deal progression. Manages operational requests, mailbox activity, data hygiene, documentation, dashboards, KPI reporting, and business reviews. Serves as a liaison between partners and Microsoft stakeholders, identifies performance trends, recommends improvements, and helps partners navigate internal processes and escalation paths.

Supports Microsoft partners across Asia by coaching investment-program usage, pipeline development, co-sell readiness, and compliance. Manages operational requests, mailbox activity, data hygiene, documentation, dashboards, KPI reporting, and business reviews. Identifies partner performance trends, recommends improvements, and coordinates with Microsoft stakeholders to resolve opportunities and escalations. Requires strong Excel skills, partner-ecosystem knowledge, cross-cultural communication, and the ability to manage priorities in a matrixed environment.

Drives Microsoft 365 Copilot trial adoption across ASEAN by enabling CSP partners and resellers, supporting customer qualification and activation, resolving adoption blockers, managing pipelines, tracking KPIs, and supporting trial-to-paid conversion. The role also delivers partner training, maintains CRM accuracy, provides performance insights, and coordinates with Microsoft teams, distributors, and resellers.

Leads customer- and partner-facing technical engagements across Microsoft Defender, Microsoft Purview, and Secure AI. Delivers security workshops, technical discussions, demos, proof-of-concept support, and Copilot for Microsoft 365 readiness sessions. Enables distributors, systems integrators, MSPs, and resellers to build Microsoft security capabilities and scale secure AI adoption. Requires strong Microsoft Security knowledge, customer-facing technical experience, fluent Bahasa Indonesia, advanced English, and the ability to communicate with technical and business audiences.

Lead customer and partner technical engagements focused on Microsoft Defender, Microsoft Purview, secure AI, and Copilot for Microsoft 365 readiness. Deliver security workshops, solution mapping, demonstrations, proof-of-concept support, and technical enablement across India. Translate requirements into secure Microsoft solution paths, support pre-sales and partner capability building, and collaborate with Microsoft sales and technical teams to accelerate secure AI adoption.

Recruit candidates internationally for technology-focused roles by partnering with hiring managers, developing sourcing strategies, engaging and screening candidates, building talent pipelines, and delivering a strong candidate experience. The role requires English and Japanese fluency, global recruiting experience, networking and negotiation skills, and familiarity with technology recruiting tools and platforms.

Own product direction for an enterprise AI platform, including requirements, roadmap, acceptance criteria, scope, and stage-gate processes. Translate customer and stakeholder needs into prioritized, testable requirements; manage trade-offs among value, velocity, leverage, and technical risk; and partner with engineering on delivery decisions. Recruit design partners, validate customer needs, document decisions, communicate with executives and clients, and maintain disciplined delivery across multiple product teams.

Lead governance, risk, and compliance activities for an enterprise AI platform. Define and mature SOC 2 and ISO 27001 controls, collect evidence, track remediation gaps, prepare audits, and create customer-facing security documentation. Partner with engineering, security, product, auditors, and client stakeholders to embed practical, automated compliance practices covering data handling, retention, access control, privacy, AI governance, and customer assurance.

Build and operate production AI capabilities, including agent runtimes, model routing, RAG, tool calling, guardrails, evaluation, monitoring, and cost and latency optimization. Develop reliable, measurable, safe AI systems; create evaluation harnesses and quality controls; monitor production behavior; and collaborate with backend, platform, product, and security teams in a client-facing consulting environment.

Designs and secures enterprise AI platform foundations for mission-critical environments. Responsibilities include threat modeling, tenant isolation, identity and authorization architecture, secure CI/CD, compliance-by-design, and protection of systems executing untrusted code, tools, or agent actions. The role partners with client engineering, product, security, and business stakeholders to deliver secure, reliable, and compliant platform capabilities.

Lead governance, risk, and compliance activities for an enterprise AI platform, including SOC 2 and ISO 27001 readiness, control definition, evidence collection, audit preparation, customer security documentation, data handling, and compliance-by-design. Partner with engineering, security, product, auditors, and client stakeholders to automate practical controls, address gaps, support assessments, and strengthen customer assurance.

Design, build, deploy, operate, and support backend services powering an enterprise AI platform. Responsibilities include developing APIs, orchestration, entitlements, tenancy, metering, integrations, governed data access, and platform services. The role requires ownership of reliable distributed systems, including testing, monitoring, failure handling, and operational support, while collaborating with client product, engineering, data, and platform stakeholders in a consulting environment.

Designs, builds, and operates cloud infrastructure and reliability capabilities for an enterprise AI platform. Responsibilities include infrastructure as code, landing zones, Kubernetes, CI/CD, observability, incident response, SLOs, production readiness, automation, cost optimization, and support for hybrid, edge, on-premises, and customer-controlled environments. This remote, client-facing consulting role requires strong communication, production ownership, and the ability to balance reliability, delivery speed, security, and operational cost.

Design, build, and operate cloud infrastructure and SRE capabilities for an enterprise AI platform. Responsibilities include infrastructure-as-code, landing zones, networking, Kubernetes, CI/CD, observability, incident response, SLOs, production readiness, automation, cost optimization, and support for hybrid, edge, air-gapped, and customer-controlled environments. The role is remote, client-facing, and requires strong collaboration and reliability ownership.

Build and operate production AI capabilities across enterprise platforms, including agent runtimes, RAG, model routing, tool calling, guardrails, evaluation, monitoring, and cost optimization. Ship reliable, safe, measurable AI features; develop evaluation frameworks and quality controls; monitor production behavior; and collaborate with client-facing product, engineering, platform, backend, and security teams to deliver practical AI solutions.

Own product direction for an enterprise AI platform, including product wedge, requirements, roadmap, acceptance criteria, scope, and stage-gate processes. Translate customer and stakeholder needs into prioritized decisions, manage technical and business trade-offs, collaborate with engineering and design partners, validate customer feedback, and communicate strategy, risks, progress, and impact to executives and clients in a consulting environment.

Design and secure enterprise AI platform foundations for mission-critical transportation and operational technology environments. Responsibilities include threat modeling, tenant isolation, identity and authorization architecture, secure CI/CD, compliance-by-design, and protection of systems executing untrusted code, tools, or agent actions. The role partners with client engineering, product, security, and business stakeholders to provide pragmatic guidance and enable reliable, compliant delivery.

Build and maintain customer-facing and administrative experiences for an enterprise AI platform. Responsibilities span front-end architecture, backend integrations, APIs, supporting services, complex B2B workflows, self-service builders, and delegated administration. The role owns features from customer problem discovery through production delivery, emphasizing usability, accessibility, performance, automated testing, quality, and maintainability. It also requires collaboration with product, design, platform engineering, clients, and external development teams in a remote consulting environment.

Designs, builds, operates, and supports backend services powering an enterprise AI platform. Responsibilities include developing APIs, AI gateway and orchestration capabilities, entitlements, tenancy models, data access patterns, integrations, and platform services. The engineer owns services throughout design, implementation, testing, deployment, monitoring, reliability, and support while collaborating with client product, engineering, data, and platform stakeholders.

Build and maintain customer-facing and administrative experiences for an enterprise AI platform. Develop front-end interfaces, APIs, backend integrations, and supporting services across the full stack. Own features from customer problem discovery through production delivery while partnering with product, design, platform engineering, and clients. Ensure usability, accessibility, performance, automated test coverage, reliability, and maintainability in a remote, client-facing consulting environment.