This role is for a highly accomplished Principal Software Engineer to join the engineering team for the Ready product, focusing on leading the technical direction, architecture, and engineering strategy for a modern, scalable, resilient, and intelligent enterprise SaaS product. You will play a key role in defining the technology stack, shaping the technical roadmap, driving architectural decisions, and leading complex engineering initiatives across multiple teams. The position requires a hands-on technical leader who can guide engineering teams through complex design decisions, troubleshoot critical technical issues, and influence the long-term evolution of the Ready product.
Responsibilities
Define and drive the architectural vision for the Ready product, ensuring scalability, resiliency, performance, maintainability, and long-term extensibility
Lead the evaluation, selection, and evolution of the core technology stack, including application frameworks, cloud-native services, database technologies, observability tools, messaging systems, and AI-enabled engineering capabilities
Define and influence the technical roadmap in partnership with engineering leadership, product management, architecture, and cross-functional stakeholders
Lead architecture reviews, design discussions, and technical decision-making for complex product and platform initiatives
Provide technical direction across multiple teams and ensure alignment with enterprise engineering standards, security expectations, and operational goals
Evaluate emerging technologies, frameworks, and engineering practices to continuously improve product capabilities, developer productivity, and system reliability
Design and build highly scalable, secure, and reliable cloud-native services using Java and related enterprise technologies
Lead the development of distributed systems, APIs, backend services, event-driven workflows, and data-intensive applications
Drive modernization initiatives that improve system performance, scalability, maintainability, and engineering velocity
Establish and promote engineering best practices around code quality, testing, automation, design patterns, performance optimization, and maintainable architecture
Lead complex cross-functional engineering initiatives that require coordination across multiple teams, systems, and stakeholders
Ensure the Ready product is built with an enterprise-level mindset, including strong consideration for scalability, compliance, security, availability, customer experience, and operational readiness
Drive platform-wide improvements in observability, monitoring, logging, metrics, tracing, alerting, and service health management
Define and implement observability standards using platforms and tools such as OpenTelemetry, Grafana, Kibana, Prometheus, Datadog, Splunk, or similar technologies
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Lead troubleshooting and root-cause analysis for complex production issues, performance bottlenecks, system failures, and reliability concerns
Partner with engineering, operations, and SRE teams to define service-level objectives, operational metrics, error budgets, incident response practices, and reliability improvement plans
Lead post-incident reviews and ensure corrective actions result in long-term improvements to architecture, automation, resiliency, and monitoring
Champion proactive engineering practices that improve product stability, reduce operational risk, and enhance customer trust
Drive performance tuning across application services, database layers, APIs, integration points, and distributed system components
Identify and resolve scalability challenges in high-volume, enterprise-grade SaaS environments
Lead capacity planning, load testing, profiling, query optimization, caching strategies, and performance benchmarking efforts
Ensure that technical designs account for throughput, latency, concurrency, data growth, resiliency, and cost efficiency
Partner with teams to establish measurable performance goals and continuously improve system responsiveness and efficiency
Bring strong insight into AI trends, AI-assisted engineering, intelligent automation, and agent-based capabilities
Drive adoption of AI tools and practices to improve software design, development, testing, documentation, troubleshooting, and operational workflows
Identify opportunities to leverage AI and agents within the engineering lifecycle and product ecosystem to improve productivity, quality, and customer value
Guide teams on responsible AI usage, including security, privacy, governance, explainability, and reliability considerations
Evaluate AI-enabled platforms, developer tools, observability assistants, coding agents, and automation frameworks that can improve engineering outcomes at scale
Provide technical leadership in database design, data modeling, query optimization, transaction management, and scalable data access patterns
Work with relational and and non-relational database technologies to support enterprise-grade application requirements
Guide teams in designing reliable, performant, and maintainable database solutions that support high-volume data processing and business-critical workflows
Lead troubleshooting of complex database performance issues, including indexing, locking, query plans, connection management, data partitioning, and schema evolution
Ensure data architecture decisions align with security, compliance, scalability, performance, and long-term maintainability goals
Champion secure software design and development practices across the Ready product
Ensure systems are designed with strong consideration for authentication, authorization, data protection, encryption, auditability, and secure integration patterns
Promote enterprise readiness through resilient architecture, operational maturity, compliance awareness, and high-quality engineering standards
Partner with security, architecture, and platform teams to ensure technical solutions align with organizational governance and risk management expectations
Mentor senior engineers, technical leads, and development teams on architecture, design, engineering practices, troubleshooting, and technical decision-making
Lead technical discussions with clarity, influence, and strong engineering judgment
Build consensus across teams on complex architecture and design decisions
Raise engineering standards through design reviews, technical coaching, documentation, knowledge sharing, and continuous improvement
Act as a trusted technical advisor to engineering leadership and cross-functional stakeholders
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
16+ years of professional software engineering experience, including significant experience building enterprise-scale software products
Strong proficiency in Java, including modern Java frameworks, backend service development, concurrency, performance tuning, and scalable application design
Deep experience with database technologies, including relational databases, SQL optimization, schema design, transaction management, indexing strategies, and performance troubleshooting
Proven experience designing and building large-scale distributed systems, microservices, APIs, and cloud-native enterprise applications
Strong understanding of observability platforms, monitoring, logging, tracing, metrics, alerting, and production diagnostics
Hands-on experience with cloud platforms such as AWS, Azure, or GCP
Experience with performance engineering, including profiling, load testing, capacity planning, caching, query optimization, and system tuning
Strong understanding of enterprise SaaS architecture, operational readiness, resiliency, availability, security, and scalability
Demonstrated ability to lead architecture discussions, define technical roadmaps, and influence engineering direction across multiple teams
Experience troubleshooting complex technical issues across application, infrastructure, database, and integration layers
Strong understanding of AI-assisted software engineering practices, AI tools, and emerging agent-based development or automation models
Excellent communication, collaboration, mentoring, and technical leadership skills
Nice to have:
Experience working on large-scale enterprise SaaS products serving global customers
Experience defining or evolving a product-level technology stack and long-term technical roadmap
Expertise with Kubernetes, containers, CI/CD pipelines, DevOps practices, and Infrastructure as Code
Experience with event-driven architecture, messaging platforms, distributed caching, and asynchronous processing patterns
Hands-on experience with observability tools such as OpenTelemetry, Grafana, Prometheus, Kibana, Splunk, Datadog, or similar platforms
Experience leading platform modernization, cloud transformation, or large-scale architecture evolution initiatives
Strong knowledge of secure software development, compliance-aware design, and enterprise integration patterns
Experience with AI coding assistants, engineering agents, intelligent automation, or AI-enabled operational tooling
Demonstrated ability to mentor senior technical talent and establish engineering standards across teams
Ability to balance strategic architecture vision with hands-on technical problem solving and delivery execution
Important Details
Travel: Up to 25%
About the Company
UKG is the Workforce Operating Platform that puts workforce understanding to work. With the world's largest collection of workforce insights, and people-first AI, their ability to reveal unseen ways to build trust, amplify productivity, and empower talent, is unmatched. This expertise equips customers with the intelligence to solve any challenge in any industry, because great organizations know their workforce is their competitive edge. UKG is proud to be an equal opportunity employer and is committed to promoting diversity and inclusion in the workplace, including the recruitment process.
