Sr Software Engineer (Java & AI-Driven Development)

NICE•Richardson, TX

8h•Hybrid

About The Position

At NICE, we're transforming how the world's leading organizations engage, support, and manage their workforce. Our Workforce Management (WFM) platform powers mission-critical operations for enterprises around the globe—and we're looking for talented engineers who want to help define what's next. We're seeking a Senior Software Engineer who thrives on solving complex technical challenges, building scalable enterprise software, and leveraging emerging AI technologies to dramatically improve engineering productivity and product quality. This is more than a traditional senior engineering role. You'll own significant product capabilities from design through production, mentor other engineers, influence architectural decisions, and help shape the AI-powered development practices that will define the future of our engineering organization. If you're excited by the idea of building sophisticated Java-based applications while pioneering how AI agents, coding tools, and automation accelerate software development, we'd love to meet you.

Requirements

8+ years of professional software engineering experience developing enterprise web applications.
Strong expertise in Java backend development, including: Spring Framework, Hibernate / JPA, RESTful Web Services, JUnit and Mockito (or similar testing frameworks)
Experience owning complex features or application components end-to-end.
Proven success designing, building, testing, and supporting production software in an Agile environment.
Experience leading technical discussions, producing design documentation, and balancing architectural trade-offs.
Strong understanding of software design principles, scalability, maintainability, and performance optimization.
Excellent communication and collaboration skills.
Hands-on experience using AI development tools such as GitHub Copilot, ChatGPT, Claude, or similar technologies.
Strong interest in applying Large Language Models (LLMs) to software engineering workflows.
Experience working with AI agents, prompts, tools, plugins, MCPs, or similar ecosystems.
Ability to leverage AI for code generation, debugging, testing, documentation, and workflow automation.
Comfortable navigating ambiguity and turning ideas into clear execution plans.
Think like owners and take accountability for outcomes.
Enjoy solving difficult technical problems.
Can confidently navigate ambiguity and create structure where none exists.
Are passionate about mentoring and helping others succeed.
Stay curious about emerging technologies and how they can create business value.
Balance innovation with pragmatism.
Bring resilience, adaptability, and a positive approach to change.

Nice To Haves

Front-end development experience with: Angular, JavaScript, HTML5, CSS, Spring MVC
Experience with: Selenium, Playwright, Cucumber
AWS cloud experience.
CI/CD experience with Jenkins and Maven.
Tomcat administration and deployment experience.
Test-Driven Development (TDD) practices.
Experience with rapid prototyping and AI-enabled development methodologies.

Responsibilities

Design, develop, and deliver scalable, high-quality software solutions for key components within our Workforce Management platform.
Take ownership of large features and services from initial concept through design, implementation, testing, deployment, and ongoing production support.
Drive technical excellence by producing thoughtful designs, evaluating trade-offs, and ensuring alignment with enterprise architecture standards.
Partner closely with Product Management, QA, Cloud Operations, Support, and Services teams to deliver customer value.
Shape and continuously improve the team's AI development ecosystem.
Design and optimize AI-assisted workflows, coding agents, prompts, reusable instructions, plugins, and tool integrations.
Help establish best practices for AI-assisted and spec-driven development.
Transform ambiguous business requirements into actionable technical specifications, implementation plans, validation criteria, and automated testing strategies.
Explore emerging AI technologies and identify opportunities to improve engineering velocity, consistency, and quality.
Develop robust unit, integration, automation, and regression testing strategies.
Troubleshoot complex production issues, conduct root-cause analysis, and implement durable solutions.
Drive engineering quality through code reviews, architectural guidance, mentoring, and technical leadership.
Identify technical risks early and proactively develop mitigation strategies.
Influence technical direction and contribute to architectural decisions across teams.
Coach engineers through design reviews, code reviews, and technical problem-solving.
Foster adoption of AI-assisted development best practices.
Help elevate engineering standards across the organization through collaboration, knowledge sharing, and mentorship.