Full-Time

Chief Architect

Legion

Legion

201-500 employees

AI-driven labor forecasting and scheduling

Compensation Overview

$300k - $385k/yr

+ Bonus + Stock Equity

Remote in USA

Remote

Bachelor's, Master's, PhD

Category
Software Engineering (1)
Required Skills
LLM
Kotlin
Microsoft Azure
Python
Forecasting
Machine Learning
Java
AWS
Go
Scala
Observability
REST APIs
Google Cloud Platform

Get referred to Legion

See people who can refer or advise you

Requirements
  • 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.
  • 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.
  • 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.
  • 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 analytics systems.
  • Experience designing highly configurable enterprise platforms without creating unbounded customization or implementation complexity.
  • Experience participating in strategic customer architecture reviews or technical due diligence with large enterprise customers.
  • Bachelor’s or Master’s degree in Computer Science or a related technical field; PhD a plus but not required.
Responsibilities
  • 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. 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. 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. 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 analytics systems. Experience designing highly configurable enterprise platforms without creating unbounded customization or implementation complexity. Experience participating in strategic customer architecture reviews or technical due diligence with large enterprise customers. Bachelor’s or Master’s degree in Computer Science or a related technical field; PhD a plus but not required.
Desired Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related technical field; PhD a plus but not required.
  • 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 analytics systems.
  • Experience designing highly configurable enterprise platforms without creating unbounded customization or implementation complexity.
  • Experience participating in strategic customer architecture reviews or technical due diligence with large enterprise customers.
  • Bachelor’s or Master’s degree in Computer Science or a related technical field; PhD a plus but not required.

Legion.co provides an intelligent automation platform for workforce management tailored to hourly workforces. It uses a proprietary WFM system to forecast demand across locations and automatically generate granular schedules. A self-learning forecasting engine keeps adapting and optimizes scheduling to match business needs with employee skills and preferences. The platform combines manager tools for compliance and engagement with employee features like gig-like flexibility, self-service, earned wage access, and rewards, all under a subscription model.

Company Size

201-500

Company Stage

Late Stage VC

Total Funding

$185.5M

Headquarters

Redwood City, California

Founded

2016

Get referred to Legion

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Dollar Tree's 150,000-associate rollout validates Legion's enterprise scale and upsell potential.
  • Rebus partnership ties Legion directly into warehouse analytics, improving real-time labor optimization.
  • Spring 2026 compliance features cover Europe, China, and seven Fair Workweek jurisdictions.

What critics are saying

  • UKG dominates retail WFM, serving 69 NRF Top 100 retailers, pressuring Legion's expansion.
  • Legion's AI stack depends on frontier-model access, creating abrupt vendor and policy exposure.
  • Dollar Tree's OSHA scrutiny and activist pressure increase implementation risk if labor outcomes disappoint.

What makes Legion unique

  • Dollar Tree chose Legion in October 2025 for 9,000 stores and 18 distribution centers.
  • July 2026 release added 90+ features, including Legion AI Upper Field Schedule Assistant.
  • WorkJam and Legion integrated scheduling, tasking, and communication for frontline operators.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Paid Vacation

Paid Holidays

Parental Leave

Company Equity

401(k) Retirement Plan

Monthly Wellness Reimbursement

Monthly Lunch on Legion

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

0%

2 year growth

0%
Associated Press
Jul 14th, 2026
Legion Technologies launches Spring 2026 release with 90+ workforce management features including AI schedule assistant

Legion Technologies has released its Spring 2026 Production Release, featuring over 90 new capabilities across its AI-native workforce management platform for hourly workers. The update introduces the Legion AI Upper Field Schedule Assistant, which helps district and area leaders oversee multiple store locations by surfacing insights and flagging issues across their portfolios. Key features include Employee Safety Management for one-tap safety check-ins, KPI Productivity Metrics that integrate real-time performance data into scheduling decisions, and Access to Hours Notifications supporting Fair Workweek compliance across seven jurisdictions. The release also adds Document Hub for centralised employee document management and expanded global compliance features for European and Chinese markets. The Redwood City-based company has received multiple industry awards for its AI-powered approach to workforce management, including recognition from the Business Intelligence Group and AI Breakthrough Awards.

Business Wire
Apr 8th, 2026
Legion appoints Carolyn Kwon Montgomery as SVP of people to support next growth phase

Legion Technologies has appointed Carolyn Kwon Montgomery as Senior Vice President of People to support its global expansion. Montgomery joins the AI-native workforce management solution provider's executive leadership team with experience building people organisations in high-growth, venture-backed companies. Most recently Chief People Officer at The Black Tux, Montgomery led people strategy for a 500-employee, multi-state workforce. She has previously achieved measurable results including increasing employee engagement by over 20% and reducing voluntary attrition by 40-50% across critical roles. At Legion, Montgomery will focus on evolving company culture, strengthening leadership development, and implementing scalable systems to support global growth. The company aims to maximise labour efficiency whilst improving conditions for hourly workers.

UC Today
Jan 21st, 2026
Legion Partners with Rebus to Bridge the Gap Between Warehouse and Workforce

Legion partners with Rebus to bridge the gap between warehouse and workforce. Legion and Rebus have joined forces to connect real-time warehouse analytics with AI-driven workforce management, giving operators a faster path from insight to action. Legion Technologies and Rebus have announced a partnership that promises to reshape how warehouses manage their workforce. The collaboration brings together Legion's AI-powered workforce management platform with Rebus' real-time warehouse analytics and labor management system, creating an integrated solution that connects operational data directly to labor planning and execution. The integration aims to tackle several pressing warehouse management issues, from employee engagement and schedule predictability to proactive workforce planning and bottleneck detection. By combining Rebus' live operational insights with Legion's automated scheduling capabilities, the solution enables warehouses to align staffing levels dynamically with actual demand, ensuring the right number of workers with the appropriate skills are deployed exactly where and when they're needed. For warehouse operators, this means moving beyond retrospective reporting to predictive, responsive workforce management that adapts to changing conditions as they unfold. Bridging the gap between warehouse insights and workforce action. The Legion-Rebus integration aims to solve a fundamental problem in modern warehouse operations: having access to critical data but lacking the mechanisms to apply it effectively to day-to-day workforce management. As Sanish Mondkar, CEO and founder of Legion, explains, "Today's logistics leaders have unprecedented access to critical warehouse data and insights - the challenge is applying that data to real-time operations." The partnership creates what Mondkar calls "a seamless path from warehouse insight to workforce action." At the heart of the solution is the connection between Rebus' data ecosystem and Legion's AI-powered scheduling and forecasting engine. When Rebus detects changes in warehouse performance metrics, throughput data, or emerging bottlenecks, this information flows directly into Legion's workforce management platform. Legion then processes these signals to automatically adjust schedules, ensuring labor alignment scales with actual demand rather than static forecasts. This real-time synchronization prevents both costly overstaffing and the operational disruptions that occur when warehouses are understaffed. The integration also transforms the employee experience on the warehouse floor. By aligning Rebus' real-time labor data with Legion's automated scheduling, workers gain schedule predictability and empowerment - factors that have become increasingly important for retention and engagement. Combined with workforce self-service features and on-demand pay capabilities accessible through a single mobile application, the solution turns raw warehouse floor data into tangible improvements in work-life balance and financial wellness - crucial advantages in high-turnover industries like warehousing. For workforce planning teams, the partnership enables a more proactive approach to labor management. Historical performance and throughput data from Rebus feed Legion's AI forecasting engine, creating a unified view of the entire operation. This gives management a clearer view of staffing trends and helps them plan budgets that more accurately reflect operational reality. When Rebus identifies bottlenecks by comparing planned work against actual execution, workforce leaders can immediately adjust staffing plans or reassign labor to maintain consistent throughput and prevent disruptions before they cascade through operations. Legion's momentum continues with major product expansion. Legion Technologies has demonstrated strong momentum entering 2026, and the Rebus partnership follows closely on the heels of another major announcement. The company recently unveiled more than 90 new innovations that significantly extend the capabilities of Legion AI. These innovations introduce autonomous workforce decision automation across forecasting, scheduling, time and attendance, and labor optimization. Central to this expansion is a new generation of AI Assistants that move beyond simple conversational interfaces. These assistants perform sophisticated, multidimensional analysis across forecasts, schedules, labor rules, and execution data. They can answer complex questions about why schedules changed, what trade-offs were made during optimization, and how alternative decisions would impact cost, coverage, compliance, and employee experience. The innovation wave also includes advanced labor planning capabilities that enable complex scenario modeling and detailed what-if analysis across demand patterns, labor constraints, and cost targets. These plans maintain a closed loop with real-time execution, continuously adapting forecasts and schedules as conditions change on the ground. Complementing these capabilities are configurable SmartCards that provide managers with personalized, actionable insights, placing the most relevant information directly at their fingertips through customizable layouts and built-in formulas. Building the future of data-driven workforce management. The Rebus partnership and the recent wave of product innovations expand the arsenal Legion Technologies offers enterprises for managing their workforce. By connecting Rebus' analytics and visibility with Legion's workforce management platform, customers can move faster from insight to action, improving labor efficiency while supporting a more flexible, employee-centric workplace. Looking ahead, the integration of real-time warehouse analytics with AI-powered workforce management sets a new standard for what's possible in logistics operations. As warehouses continue to face pressure from volatile demand patterns and the need to improve profitability, solutions that can dynamically align staffing to actual operational conditions in real time will become increasingly valuable.

Retail TouchPoints
Oct 16th, 2025
Dollar Tree Deploys Workforce Management Solution Chainwide

Dollar Tree deploys workforce management solution chainwide. * October 16, 2025 at 10:46 AM EDT * By Adam Blair Value retailer Dollar Tree has partnered with Legion Technologies to launch its first-ever workforce management solution, covering employees at its 9,000 stores and 18 distribution centers across North America. With the Legion mobile app, associates can request schedule changes, swap shifts, communicate with managers and access performance rewards and feedback via a single user interface. "As a retailer with over 150,000 associates, we needed a next-generation solution that would allow us to better manage our labor budget while increasing associate engagement," said Jocelyn Konrad, Chief of Dollar Tree Stores and Enterprise Operations in a statement. "With Legion's support, we are enhancing our workforce operations to improve our associate workflows while delivering genuine value for our business." "The platform also enhances compliance through powerful automation and visibility tools across multiple jurisdictions, while delivering advanced demand forecasting to optimize labor utilization and ensure appropriate staffing levels," said Sanish Mondkar, CEO of Legion Technologies in a statement. In May 2023 Dollar Tree faced pressure from activist investors over low worker pay and a lack of diversity in upper levels of management, and the retailer has also come under fire with the U.S. Department of Labor's Occupational Safety and Health Administration (OSHA) for workplace safety violations. In August 2025 Dollar Tree partnered with Uber Eats for on-demand deliveries from its stores, but these store-based deliveries often put additional pressure on associates, increasing the need for workforce and task management solutions.

Team IT Security
Jul 30th, 2025
Legion Raises $38M for AI SOC Platform

Legion has emerged from stealth mode, securing $38 million in seed and Series A funding for its browser-native AI Security Operations Center (SOC) platform.