Own end-to-end architecture for the AI application: domain model, APIs, UX/backend integration, data flows, and cloud/Kubernetes topology
Define and implement multi-tenancy and isolation strategy (pooled vs. siloed vs. VPC), regionalization, and tenant-aware observability/support
Establish SLAs/SLOs, rate limits/quotas, HA/DR, and resilience testing (chaos/failover); drive SLO/error-budget practices
Build commercialization enablers: SSO (SAML/OIDC), SCIM provisioning, fine-grained RBAC/ABAC/DBAC, a zero-trust architected entitlement service
Stand up ML Ops: data pipelines, feature store, model registry, CI/CD for ML, offline/online eval harness, model rollback/kill switches, human-in-the-loop workflows
Security & privacy by design: threat modeling (including AI-specific risks), secrets/KMS, encryption at rest/in transit, audit logging, data retention/deletion, PII handling, secure SDLC controls (SAST/DAST/SBOM)
Define BU architecture principles, capability map, and target state; publish reference architectures and an approved tech catalog
Set identity and integration standards (API/eventing), data governance (lineage, quality, residency), and IaC patterns; create “paved roads” (golden templates for services, pipelines, observability, security checks, w/ auditability)
Spin-out readiness: design boundary APIs with the parent company, plan data partitioning and key management
Establish lightweight governance (Architecture Decision Records (ADRs), design reviews, fast exceptions) that enables speed while managing risk
Mentor & support engineers on the team.

Requirements

Minimum Bachelor's ideally Master's degree in Computer Science
10+ years in software architecture/engineering
5+ years leading architecture for customer-facing SaaS products
Strong familiarity with AI and ML concepts
Demonstrated experience shipping multi-tenant (or VPC-isolated) SaaS with defined SLAs and business customers
Deep cloud/platform skills: containers/Kubernetes, IaC (e.g., Terraform), networking, CI/CD, observability, performance/cost optimization
Security/compliance expertise: threat modeling, secure SDLC controls (SAST/DAST/SBOM), identity (OIDC/SAML) and provisioning (SCIM), audit logging; SOC 2 readiness or operation
Data and AI/ML systems: data pipelines/governance, model lifecycle and MLOps, evaluation/guardrails, responsible AI practices
Product mindset: understands packaging/entitlements, usage metering, versioning/compatibility, and impact on margins and customer experience
Excellent communication and influence across executives, customers, and engineers; ability to create clarity and drive decisions in ambiguity.

Benefits

Medical, dental, vision, basic and supplemental life insurance
Paid parental leave
Short and long-term disability
401(k) with a company match of up to 5%
Education Support Program
Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

software architectureAI conceptsML conceptsmulti-tenancySaaScloud computingKubernetesCI/CDdata pipelinessecurity controls

Soft Skills

communicationinfluencementoringdecision-makingclarity in ambiguity

Certifications

Bachelor's degreeMaster's degreeSOC 2 readiness