Chief Architect

Chief Architect Remote - US Legion Technologies is building the AI-powered operating system for the hourly workforce. We are hiring a Chief Architect to serve as Legion’s most senior hands-on technical leader and to shape the technical foundation that will power the next decade of product innovation. This is not a strategy-only or advisory role. The Chief Architect must live close to the code, go deep with engineering teams, challenge assumptions, write and review technical designs, make high-consequence architecture decisions, and help turn bold product ambitions into scalable, reliable production systems. This person will own architecture and technical decision-making for the most complex parts of Legion’s Workforce Management platform, including AI, optimization, forecasting, scheduling, distributed systems, data platforms, real-time decisioning, enterprise scalability, security, compliance, and developer productivity. The ideal candidate has built and scaled mission-critical software used by large enterprise customers, has deep technical credibility with senior engineers, and can operate fluidly between code-level decisions and long-term platform strategy. They are pragmatic, decisive, opinionated, and comfortable making hard tradeoffs when simplicity, scalability, reliability, or customer trust require it. This role reports to the Head of Product, Engineering, and Support. This is an open role currently being filled on an interim basis by the CEO. Responsibilities and Duties Hands-On Architecture and Technical Decision-Making Serve as Legion’s senior-most hands-on technical authority for complex architecture, system design, and platform evolution. • Personally dive into code, design documents, production incidents, performance bottlenecks, and implementation tradeoffs to diagnose root causes and guide technical direction. • Lead the hardest technical decisions across AI systems, optimization engines, distributed systems, data architecture, reliability, scalability, security, and platform modernization. • Write prototypes, reference implementations, architecture decision records, technical specifications, and design patterns where needed to unblock teams and establish clear direction. • Make high-consequence technical decisions with incomplete information, balancing correctness, simplicity, speed, scalability, reliability, cost, and long-term maintainability. • Challenge architectural drift, unnecessary complexity, weak abstractions, and short-term decisions that create long-term platform risk. • Partner directly with Staff, Principal, and senior engineering leaders in design reviews, code-level discussions, and implementation planning. Platform Architecture and Technical Vision • Define and own the long-term architecture for Legion’s AI-driven Workforce Management platform across application services, data infrastructure, ML systems, optimization engines, APIs, integration architecture, developer platforms, and enterprise-scale operations. • Establish engineering-wide standards for system design, scalability, performance, reliability, extensibility, observability, security, and maintainability. • Serve as the final architectural authority for major platform initiatives and technical decisions with long-term consequences. • Identify opportunities to reduce complexity, improve system efficiency, accelerate engineering velocity, and unlock new product capabilities. • Proactively surface technical debt, architectural risk, and platform constraints before they compound into customer, product, or engineering velocity issues. • Create pragmatic migration paths from current-state architecture to target-state architecture while maintaining uptime, customer trust, backward compatibility, and delivery speed. • Ensure Legion’s architecture supports enterprise configurability and extensibility without allowing uncontrolled customization or product fragmentation. AI, Optimization, and Decision Systems • Architect AI-native product capabilities across forecasting, scheduling, labor optimization, recommendations, copilots or agents, anomaly detection, decision automation, and other intelligent workforce management use cases. • Define the architecture for production AI systems, including data pipelines, feature platforms, model training, model serving, retrieval, evaluation, monitoring, feedback loops, and continuous improvement. • Make clear build-versus-buy decisions across LLMs, classical ML, optimization solvers, retrieval systems, evaluation frameworks, and internal AI platforms. • Partner closely with Product, Data Science, and Engineering to turn mathematically complex labor optimization problems into reliable, scalable, explainable production systems. • Establish standards for AI system quality, including accuracy, latency, cost, explainability, drift detection, reliability, customer-specific behavior, and production observability. • Ensure Legion’s AI capabilities remain differentiated, defensible, enterprise-ready, and deeply integrated into operational workflows rather than bolted on as superficial features. Distributed Systems, Data, and Enterprise Scale • Drive architecture for large-scale, multi-tenant SaaS systems serving complex enterprise customers with high availability, performance, security, and compliance expectations. • Lead technical decisions involving microservices, APIs, event-driven architecture, distributed data processing, real-time systems, data governance, and large-scale analytics. • Improve the architecture for observability, incident analysis, performance engineering, capacity planning, reliability, and operational excellence. • Use production data, incidents, escalations, and customer operational patterns as inputs into architecture and platform improvement. • Ensure architectural decisions support global scale, data residency, enterprise integrations, configurability, extensibility, and long-term platform leverage. Product, Business, and Customer Impact • Connect technical decisions directly to customer value, product velocity, implementation speed, scalability, reliability, and long-term platform advantage. • Partner with Product and Engineering leadership to translate ambitious product goals into executable architecture and technical roadmaps. • Understand enterprise customer complexity and design systems that support real-world operational variability without creating unsustainable technical debt. • Support strategic customer, partner, and vendor architecture discussions where deep technical credibility is required. • Help evaluate technical implications of major product, partner, platform, and commercial decisions. Engineering Culture and Technical Talent • Mentor and elevate Staff Engineers, Principal Engineers, architects, and senior engineering leaders across the organization. • Raise the bar for technical judgment, system design, architecture reviews, documentation, code quality, operational discipline, and engineering craftsmanship. • Help assess, attract, and develop senior technical talent, including Staff, Principal, and architect-level engineers. • Build a culture of disciplined technical thinking, direct debate, clear decision-making, and pragmatic execution. • Ensure architectural decisions are documented clearly, understood broadly, and translated into executable engineering plans. Security, Compliance, and Enterprise Readiness • Own the architectural approach to enterprise security, data governance, privacy, compliance, auditability, and resilience. • Ensure architecture supports SOC 2, ISO 27001, data residency, access control, tenant isolation, regulatory requirements, and other needs of large global enterprise customers. • Partner with Security, Infrastructure, Product, and Engineering teams to make security and compliance foundational architectural properties rather than after-the-fact controls. Travel Requirements • Up to 15% travel for leadership collaboration, engineering offsites, strategic customer engagements, and other business-critical meetings. Required Skills and Qualifications Experience Level 15+ years of experience building and scaling large-scale software systems.Prior experience as a Chief Architect, Distinguished Engineer, Principal Architect, very senior Principal Engineer, or equivalent senior technical leadership role. • Demonstrated success designing and scaling mission-critical, multi-tenant SaaS platforms for enterprise customers. • Deep hands-on experience with large-scale distributed systems, cloud-native architecture, data platforms, APIs, event-driven systems, platform engineering, and high-availability production environments. • Proven ability to operate as a hands-on technical leader who can credibly engage in code-level and design-level discussions with senior engineers. • Experience making major architecture decisions for systems with high scale, high reliability requirements, complex domain logic, and long product lifecycles. • Experience modernizing large production systems incrementally while maintaining uptime, backward compatibility, customer trust, and engineering velocity. • Experience building or supporting AI, ML, optimization, decisioning, forecasting, or data-intensive products in production. • Strong understanding of observability, incident response, performance engineering, reliability architecture, capacity planning, and operational excellence. • Ability to communicate complex technical concepts clearly to engineering teams, executives, customers, and cross-functional partners. Technical Depth • Deep expertise in distributed systems, system design, cloud architecture, service-oriented or microservices architectures, APIs, event-driven systems, and large-scale data processing. • Strong experience with cloud platforms such as AWS, GCP, or Azure. • Strong experience with modern engineering practices, including architecture reviews, design documents, code reviews, testing strategy, deployment architecture, observability, and production operations. • Experience with languages such as Java, Kotlin, Go, Python, Scala, or similar modern backend languages. • Ability to reason deeply about tradeoffs involving performance, latency, throughput, cost, reliability, developer productivity, extensibility, and maintainability. Leadership and Judgment • Strong architectural judgment: knows when to simplify, when to re-platform, when to tolerate debt, and when to force a hard technical reset. • Demonstrated ability to make bold technical decisions with incomplete information and drive alignment across senior technical and executive stakeholders. • Ability to influence without relying on hierarchy, while still being willing to make clear decisions when consensus is insufficient. • Strong product and business judgment; able to connect architecture decisions to customer outcomes, implementation speed, product differentiation, and company strategy. • Pragmatic builder mindset: balances long-term architecture with startup speed, customer urgency, and execution realities. Preferred Qualifications and Attributes • Experience building platforms used by millions of users or supporting very large-scale enterprise operations. • Experience at companies known for large-scale distributed systems, AI, cloud infrastructure, enterprise SaaS, workforce management, supply chain, fintech, commerce, logistics, or other complex operational domains. • Familiarity with optimization engines, scheduling algorithms, forecasting systems, constraint solvers, real-time decision systems, or mathematically complex production systems. • Experience architecting AI-native product capabilities, including LLM-enabled workflows, AI agents or copilots, model evaluation, retrieval systems, feedback loops, and production monitoring. • Experience building internal developer platforms, platform infrastructure, data platforms, ML pipelines, or large-scale analyti…