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Software Engineer- Payroll Platform

Job in Lowell, Middlesex County, Massachusetts, 01856, USA
Listing for: UKG
Full Time position
Listed on 2026-09-20
Job specializations:
  • Software Development
    Software Architect, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 130000 - 160000 USD Yearly USD 130000.00 160000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer- Payroll Platform

Technical Strategy & Architecture

Define and drive the long-term technical vision, architecture, and modernization strategy for Payroll platforms and services. Lead the design and evolution of highly scalable, resilient, secure, and maintainable distributed systems. Establish architectural standards, engineering best practices, and technical governance across multiple teams. Evaluate emerging technologies, including AI and Generative AI solutions, and drive adoption where they create measurable business value. Serve as a technical leader across engineering teams, influencing architecture and engineering decisions beyond immediate team boundaries.

Partner with Engineering Managers, Product Leaders, Architects, and Principal Engineers to align technical strategy with organizational priorities. Lead technical discovery, proof‑of‑concepts, and platform initiatives that span multiple products and services. Drive engineering excellence through technical reviews, architecture assessments, and continuous improvement initiatives.

Software Engineering Excellence

Contribute hands‑on development for complex and business‑critical initiatives. Champion software quality, observability, performance, security, and operational excellence throughout the software development lifecycle. Establish standards for testing, automation, deployment, and production readiness. Lead resolution of complex production incidents and conduct root cause analysis to improve platform resilience.

AI and Innovation

Identify and implement opportunities to leverage AI technologies, including Large Language Models (LLMs), machine learning, and intelligent automation. Partner with product and engineering teams to incorporate AI‑powered capabilities into payroll products and internal engineering workflows. Evaluate AI governance, security, scalability, and operational considerations for enterprise adoption.

Mentorship & Talent Development

Mentor senior and emerging engineers across the organization. Foster a culture of technical excellence, innovation, inclusion, and continuous learning. Influence hiring, onboarding, technical career development, and succession planning.

Dev Ops & Operational Ownership

Champion end‑to‑end ownership from requirements through production operations. Drive improvements in reliability, observability, deployment automation, and service health. Define and monitor key operational metrics and service‑level objectives (SLOs).

Collaboration & Communication

Communicate complex technical concepts effectively to engineering, product, and executive stakeholders. Build consensus across teams and drive alignment on technical direction and priorities. Represent engineering in strategic planning discussions and cross‑functional initiatives.

Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 10+ years of professional software engineering experience, including significant experience designing and operating large‑scale distributed systems.
  • Expert‑level proficiency in Java and modern backend architecture patterns.
  • Strong experience with React, Type Script, and modern web application architectures.
  • Deep understanding of microservices, event‑driven systems, APIs, and enterprise integration patterns.
  • Extensive experience with SQL and No

    SQL databases and large‑scale data architectures.
  • Strong expertise in cloud‑native technologies and platforms such as Azure, AWS, or Google Cloud Platform.
  • Proven experience leading architectural initiatives across multiple teams or product areas.
  • Experience implementing observability, reliability engineering, and operational excellence practices.
  • Familiarity with AI technologies, Generative AI, LLM platforms, AI‑assisted…
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