Enterprise Architect

Staritas• Remote, US,

10h•$155,000 - $185,000•Remote

About The Position

Staritas is seeking an experienced Enterprise Architect to lead enterprise technology modernization, platform scalability, and responsible AI enablement. Reporting to the CTO, this role will shape architecture strategy across applications, cloud platforms, APIs, integrations, data, cybersecurity, DevOps, and engineering practices. This role partners with technology, business, product, engineering, and security leaders to design secure, scalable, reliable, and maintainable solutions. The Enterprise Architect will help reduce technical debt, improve delivery speed, strengthen platform resilience, and enable practical AI adoption across the enterprise.

Requirements

Bachelor’s or master’s degree in Computer Science, Information Technology, Engineering, or equivalent experience.
10+ years of progressive technology experience in enterprise architecture, solution architecture, software engineering, systems integration, cloud platforms, or technical leadership.
Hands-on experience with REST APIs, API-first design, modular or microservices architectures, messaging, data flows, and enterprise integration patterns.
Experience with Docker, Kubernetes, Linux, CI/CD, automated testing, and DevOps automation.
Strong understanding of data architecture, databases, cybersecurity, IAM, observability, disaster recovery, and operational resilience.
Ability to lead architecture reviews, influence technical direction, mentor engineers, and communicate with technical and non-technical stakeholders.
Practical experience using AI tools to improve engineering, architecture, documentation, testing, troubleshooting, or productivity.

Nice To Haves

Experience modernizing, consolidating, or scaling enterprise platforms.
Experience with AWS, Azure, GCP, or similar cloud platforms.
Experience with enterprise SaaS ecosystems, ERP, CRM, workflow, analytics, data warehouse, or lakehouse platforms.
Relevant architecture, cloud, Kubernetes, security, or enterprise technology certifications.
Experience with AI platforms, LLM integrations, AI coding assistants, RAG, AI agents, enterprise knowledge connectors, or AI governance practices.

Responsibilities

Define and drive enterprise architecture, platform modernization, AI enablement, and governance roadmaps.
Lead current- and future-state planning across applications, integrations, APIs, cloud, data, security, DevOps, observability, and AI-enabled capabilities.
Design secure, scalable, API-first, cloud-ready, and AI-aware architecture patterns.
Provide architecture leadership for enterprise applications, workflow systems, data platforms, integrations, identity, monitoring, and deployment automation.
Establish architecture standards, reusable patterns, decision records, and lightweight governance practices.
Review solution designs, validate technology choices, identify risks, reduce technical debt, and guide implementation.
Mentor engineering teams on CI/CD, automated testing, containers, Kubernetes, DevOps automation, secure development, observability, and AI-assisted workflows.
Partner with security and risk stakeholders on secure architecture, access controls, data protection, secure SDLC practices, and responsible AI usage.
Champion responsible AI adoption to improve software delivery, engineering productivity, automation, analytics, operations, and knowledge management.
Help teams use AI for code generation, code review, refactoring, testing, documentation, architecture analysis, troubleshooting, and research.
Develop responsible AI standards for data protection, secure prompting, model selection, human review, acceptable use, auditability, cost, and risk management.
Identify high-value AI use cases and define architecture patterns for AI integrations, including APIs, workflow automation, retrieval-augmented generation, enterprise knowledge connectors, and human-in-the-loop review.