Lead AI Platform Architect – Workflows, Automation & Multi-Tenant SaaS

About The Role

We are looking for a highly capable, platform-first engineering leader who can help us evolve our current product into a scalable, production-grade AI platform.

This is not a feature-delivery-only role, and it is not a narrow full stack role. We need someone who can architect, build, standardize, and scale the full platform framework across backend systems, frontend systems, AI pipelines, multi-agent workflows, proctoring flows, speech systems, computer vision applications, safe AI systems, deployment, automation, observability, and multi-tenant SaaS infrastructure.

The person in this role will go beyond shipping features. They will help define the overall framework, architecture, implementation standards, technical direction, and execution model required to deliver and scale multiple intelligent product flows.

We are looking for someone who is both tech-first and business-aware: someone who understands how to build the right systems, prioritize what matters, and lead engineering execution across architecture, implementation, reliability, and delivery.

What Will You Own

• Lead the evolution of our product from a tool into a scalable, modular, production-grade platform
• Define and drive overall architecture across frontend, backend, AI, data, infrastructure, and operations
• Build and standardize engineering frameworks, reusable components, implementation patterns, and delivery standards
• Ensure the platform is scalable, secure, extensible, observable, and maintainable
• Drive long-term architecture and execution, not just short-term feature development
  

• Design and implement AI-powered platform frameworks that support multiple workflows and use cases
• Build and manage multi-agent systems, orchestration layers, model interactions, context handling, and structured task flows
• Integrate and productionize multiple AI capabilities including LLMs, text-to-speech, speech-to-text, computer vision, and workflow automation
• Build safe, reliable, and traceable AI systems with guardrails, monitoring, fallbacks, feedback loops, and evaluation mechanisms
• Define standards for prompts, model routing, structured outputs, fine-tuning or adaptation layers, and AI performance measurement
  

• Build proctoring as part of the broader platform framework, not as a standalone workflow
• Design and integrate AI-driven proctoring flows using multiple services and signals such as computer vision, speech analysis, event detection, review logic, flagging, tracking, and feedback
• Create platform-level frameworks for speech systems, audio workflows, computer vision pipelines, and safe AI controls
• Ensure critical AI workflows are auditable, traceable, monitored, and aligned to platform standards
• Build systems that support human review, policy-aware controls, exception handling, and operational visibility
  

• Lead development across frontend applications, backend services, APIs, internal tools, orchestration layers, and data systems
• Build product-grade user experiences using React / Next.js / TypeScript
• Build scalable backend systems using Node.js and/or Python
• Create modular services, shared components, reusable APIs, and extensible internal frameworks
• Translate complex business and AI requirements into stable, production-ready systems
  

• Architect and implement multi-tenant SaaS foundations
• Own deployment architecture, CI/CD, release processes, environment management, and automation
• Build systems for monitoring, alerting, analytics, usage tracking, and feedback capture
• Improve engineering velocity, system reliability, and delivery quality across teams
• Lead technical execution across multiple product and AI streams from architecture through production readiness
  

• Lead engineers and guide implementation quality, architecture decisions, and delivery discipline
• Translate business goals into technical systems, priorities, and execution plans
• Work closely with product, design, business, and leadership stakeholders
• Create clarity across complex workflows and drive high-quality outcomes across multiple streams
• Help shape the engineering culture, standards, and platform roadmap

Key Responsibilities

• Architect the platform end to end across application, AI, data, and infrastructure layers
• Build the overall framework for scalable AI product development, workflow orchestration, and system delivery
• Lead implementation of backend systems, frontend applications, APIs, orchestration services, and platform modules
• Design and integrate multiple AI capabilities including LLM workflows, multi-agent systems, text-to-speech, speech-to-text, computer vision, proctoring flows, and safe system controls
• Establish standards for implementation quality, architecture, observability, evaluation, deployment, and reliability
• Build monitoring, tracking, analytics, feedback, and auditability into all critical workflows
• Create reusable frameworks that allow multiple AI-enabled product flows to be developed and scaled on the same platform
• Drive production readiness, operational visibility, and long-term maintainability
• Lead technical execution across architecture, implementation, productionization, and continuous improvement
• Align technical decisions with product and business priorities

Required Experience

• 7–12 years of experience in platform engineering, backend systems, full stack product development, or scalable SaaS architecture
• Proven experience building production-grade platforms and frameworks, not only isolated features
• Strong hands-on experience in frontend, backend, APIs, and data systems
• Strong expertise in:
• React / Next.js / TypeScript
• Node.js and/or Python
• API architecture and service design
• PostgreSQL / MySQL or equivalent production databases
• Deep understanding of:
• system architecture
• scalable backend design
• multi-tenant SaaS systems
• deployment workflows and CI/CD
• automation and orchestration
• observability, logging, monitoring, and operational systems
• Experience building or integrating AI-driven applications and workflow-based systems in production
• Strong understanding of AI pipelines and orchestration across multiple components such as LLMs, speech systems, computer vision, automation layers, and monitoring systems
• Ability to lead end-to-end execution from architecture and framework design through implementation and delivery
• Strong product and business understanding, with the ability to prioritize and build for real-world platform outcomes

Strongly Preferred

• Experience with multi-agent systems and agentic workflow frameworks
• Experience with proctoring systems, monitoring systems, review pipelines, or AI-driven operational workflows
• Experience with text-to-speech, speech-to-text, audio intelligence, or voice-enabled product flows
• Experience with computer vision applications and real-time or event-driven AI pipelines
• Experience building safe, monitored, auditable AI systems with human-in-the-loop controls
• Experience with RAG, vector databases, evaluation systems, fine-tuning workflows, or model adaptation frameworks
• Experience with workflow engines, task queues, or event-driven architectures
• Experience with cloud platforms such as GCP
• Experience with Docker, infrastructure automation, and production deployments
• Experience leading engineers or owning technical direction across multiple engineering streams

Who Will Succeed in This Role

We are looking for someone who:

• thinks like a platform owner, not only a developer
• can operate across architecture, engineering, AI systems, and execution
• is comfortable working across business priorities and deep technical detail
• can build, improve, standardize, and scale
• can lead teams while staying hands-on
• cares deeply about reliability, monitoring, feedback loops, and quality of delivery
• can manage complexity across multiple AI and product workflows
• accepts challenges realistically and does not overpromise to deliver unrealistic stuff

What You'll Get

• Opportunity to shape and build a core AI platform from the ground up
• High ownership across product, platform, and technical direction
• Real exposure to multi-agent systems, proctoring frameworks, speech and vision applications, and scalable SaaS platform design
• Direct collaboration with leadership on architecture, delivery, and growth
• A role with room to grow into broader engineering leadership