Staff Software Engineer-JAVA

UKG; Lowell (MA); On-site; USD 140,000 - 180,000; Full time

Job summary

UKG in Lowell, MA seeks a senior Java software engineer to design, develop, test, and maintain scalable enterprise SaaS applications. You will work across the stack, integrating AI features, LLMs, RAG, and MLOps patterns while ensuring code quality, security, and performance.

You will collaborate with product, UX, QA, DevOps, and security teams, apply TDD, CI/CD, and modern patterns, and mentor peers in engineering excellence. 5+ years of hands-on Java experience required.

Qualifications

• 7+ years of hands-on experience developing enterprise Java-based web applications.
• Proven expertise with Java, J2EE, Spring Boot, Spring Framework, Hibernate/JPA, React, JavaScript, HTML5, CSS3, REST APIs, Microservices, SQL, and MVC architecture.
• Strong experience integrating AI capabilities (LLMs, RAG, embeddings) and deploying AI agents in enterprise SaaS.
• Experience with cloud platforms (AWS/Azure/GCP) and container orchestration (Kubernetes, Docker, OpenShift).
• Familiarity with CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps) and observability tools (Datadog, Grafana, OpenTelemetry).
• Knowledge of secure coding, testing (TDD/CI), and scalable architecture for SaaS platforms.

Responsibilities

• Design, develop, test, and maintain scalable Java-based web applications and platform services.
• Build RESTful APIs and microservices supporting enterprise SaaS applications.
• Integrate AI features, LLMs, RAG, semantic search, and AI orchestration for workflows.
• Mentor teammates, conduct code reviews, and promote engineering excellence.
• Coordinate with Product, UX, QA, DevOps, Security for reliable deployments.
• Ensure security, performance, observability, and maintainability across the stack.

Skills

Java

Spring Boot

React

JavaScript

HTML5

CSS3

REST APIs

Microservices

SQL

CI/CD

AWS

Azure

GCP

Kubernetes

Docker

OpenShift

Terraform

LLMs

RAG

AI integration

Education

BS in CS

MS in CS

Tools

GitHub Actions

Jenkins

OpenTelemetry

Datadog

CloudWatch

Terraform

Kubernetes

Job description

Job Description

Design, develop, test, and maintain scalable Java-based web applications and platform services. Build high-quality, secure, scalable, and maintainable software following modern software engineering principles and best practices. Demonstrate an excellent understanding of object-oriented programming, design patterns, algorithms, distributed systems, and software architecture. Develop both front-end and server-side components using Java, Spring Boot, React, JavaScript, HTML5, CSS3, SQL, Hibernate/JPA, and related technologies. Design and implement RESTful APIs and microservices supporting enterprise SaaS applications. Build, integrate, and maintain AI-powered features, including Large Language Model (LLM) integrations, Retrieval-Augmented Generation (RAG), semantic search, prompt orchestration, and intelligent workflow automation where appropriate. Design, develop, and optimize AI Agents to automate engineering and business workflows using modern agent frameworks, tool integrations, and enterprise security best practices. Leverage AI-assisted software development tools (such as GitHub Copilot, ChatGPT, Cursor, Claude, or equivalent) to improve engineering productivity while maintaining high standards for code quality, security, testing, and maintainability. Evaluate emerging AI technologies and recommend practical adoption opportunities that improve developer productivity, platform capabilities, and customer experience. Work autonomously on complex technical issues requiring analysis across the application stack, including browser, APIs, application services, databases, cloud infrastructure, and third-party libraries. Contribute to the design, implementation, and maintenance of core platform infrastructure services supporting highly available SaaS applications. Apply software design patterns and common algorithms to build robust, scalable, and efficient solutions. Perform insightful and constructive code reviews to maintain engineering excellence, mentor team members, and minimize regression defects and technical debt. Write comprehensive Unit Tests, Integration Tests, and API Automation Tests for new features following Test‑Driven Development (TDD) and Continuous Integration (CI) best practices. Troubleshoot and resolve complex production issues through root cause analysis across applications, infrastructure, cloud services, and third-party integrations. Collaborate effectively with Product Management, UX, QA, DevOps, Security, and cross‑functional engineering teams. Continuously improve application architecture, performance, scalability, observability, security, and development processes. Champion engineering excellence through clean code, secure coding standards, automation, performance optimization, AI-assisted development, and continuous improvement. BS/MS degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience. 7+ years of hands‑on experience developing enterprise Java-based web applications. Strong experience with Java, J2EE, Spring Boot, Spring Framework, Hibernate/JPA, React, JavaScript, HTML5, CSS3, REST APIs, Microservices, SQL, and MVC architecture. Strong SQL experience, including Stored Procedures, Functions, Triggers, Views, and query optimization. Strong understanding of Test‑Driven Development (TDD), automated testing, CI/CD pipelines, and software quality best practices. Proven track record of delivering high‑quality, scalable software solutions on time. Experience building and deploying AI Agents using modern frameworks such as LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, or equivalent. Experience integrating Large Language Models (LLMs) into enterprise applications using OpenAI, Anthropic, Google Gemini, or similar platforms. Experience implementing Retrieval‑Augmented Generation (RAG), vector databases, embeddings, prompt engineering, Model Context Protocol (MCP), tool calling, and AI orchestration frameworks. Demonstrated ability to leverage AI‑assisted development tools to improve software quality, engineering productivity, testing, documentation, and code optimization while adhering to engineering best practices. Understanding of responsible AI practices, prompt security, data privacy, AI governance, and AI evaluation methodologies. Experience implementing, managing, and improving deployments across private and public cloud platforms supporting enterprise SaaS applications. Experience developing infrastructure automation and platform tooling to improve scalability, reliability, deployment speed, and operational efficiency. Experience with AWS, Microsoft Azure, or Google Cloud Platform. Experience with Kubernetes, Docker, OpenShift, or other container orchestration technologies. Experience with Infrastructure as Code (Terraform, CloudFormation, ARM Templates, or equivalent). Experience building and maintaining CI/CD pipelines using GitHub Actions, Jenkins, Azure DevOps, GitLab CI, or similar tools. Experience implementing monitoring and observability solutions using Datadog, Grafana, Prometheus, Splunk, OpenTelemetry, or equivalent platforms. Experience automating operational processes using Bash, Python, PowerShell, APIs, and infrastructure automation tools. Experience troubleshooting distributed systems across application, infrastructure, networking, and cloud environments. Strong focus on application performance optimization, scalability, reliability, security, and operational excellence.