Principal Architect, Platform

About the role

The Principal Architect, Platform is one of the most important hires interos.ai is making right now. Reporting directly to our SVP of Engineering, this role sits at the center of our next phase of growth, owning the architecture of the enterprise-grade scalable platform that will power interos.ai's product vision to drive proactive supply chain risk mitigation. This is a hands-on individual contributor role with organization-wide technical influence.

Responsibilities

• Define and own the long-term technical architecture of the interos.ai platform, including microservices topology, data infrastructure, API contracts, event streaming, and platform scalability strategy
• Own the architectural decision-making process across Engineering, reducing cycle time on design questions by establishing clear patterns, precedents, and guardrails that empower teams to move fast without going back to first principles every time
• Lead architectural design reviews across Engineering teams, setting standards for system design, inter-service communication, data modeling, and platform extensibility
• Partner with Product and Engineering leadership to translate product roadmap into architectural requirements, identifying technical risk, sequencing trade-offs, and enabling teams to move with speed and confidence
• Design and champion platform capabilities that are foundational to multiple product areas, including multi-tenancy, data pipeline architecture, search and graph infrastructure, and platform observability
• Establish and maintain engineering standards, and reference architectures that enable consistent, high-quality engineering across teams
• Identify and address systemic technical debt, leading initiatives to modernize, simplify, or replace components that limit platform scalability or developer velocity
• Collaborate with the Security Architect to ensure security and compliance requirements are addressed at the architecture layer, with a particular focus on FedRAMP, IL4/IL5, and enterprise customer trust requirements
• Represent interos.ai's technical architecture in conversations with enterprise customers, partners, and prospects where platform scalability, reliability, and security are part of the buying decision
• Stay current on industry trends in distributed systems, cloud-native architecture, AI/ML platform patterns, and data engineering, bringing relevant innovations back to the team

Requirements

• 12+ years of software engineering experience, with at least 5 years in a senior architecture or staff/principal engineering role at a cloud-native SaaS company
• Deep expertise designing and operating large-scale distributed systems, including microservices architecture, event-driven design, and API platform strategy
• Hands-on experience with data platform architecture, including streaming pipelines (Kafka or equivalent), graph data models, search infrastructure (Elasticsearch or equivalent), and large-scale data processing
• Proven ability to define and drive architectural strategy across multiple engineering teams, influencing without direct authority
• Experience with multi-tenant SaaS architecture, including tenant isolation, data partitioning, and scalability patterns for enterprise customers
• Track record of making and documenting significant architectural decisions with clear rationale, trade-off analysis, and long-term thinking
• Strong engineering fundamentals across systems design, reliability engineering (SLIs, SLOs, SLAs), and platform observability (logging, metrics, tracing)
• Excellent written and verbal communication skills, with the ability to explain complex architectural concepts to both technical and non-technical audiences
• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent experience
• A design philosophy grounded in simplicity — you believe the best architectures are the easiest to understand, and you have a track record of taking complex systems and making them elegantly simple

Qualifications

• Experience architecting platforms for federal government customers, including familiarity with FedRAMP, IL4/IL5, or DoD cloud security requirements
• Background in supply chain intelligence, risk analytics, or graph-based data platforms
• Experience with AI/ML platform infrastructure, including model serving, feature stores, and MLOps pipelines
• Familiarity with Kubernetes and container orchestration at scale
• Contributions to open source projects or external technical writing, conference talks, or other evidence of thought leadership in the distributed systems or platform engineering space