Software Engineer II

As a Software Engineer II within Next Gear Capital
, you will help build and evolve the systems, applications, and digital capabilities that power one of the automotive industry's leading inventory finance businesses. Working as part of a collaborative product and engineering team, you'll contribute to solutions that support critical business operations, improve customer experiences, and enable the next generation of technology-driven innovation across the organization.

This role is ideal for an engineer who has moved beyond purely guided execution and is ready to take ownership of discrete features and system components while continuing to grow technical depth and business understanding. You will work closely with product managers, architects, engineers, and business stakeholders to design, build, test, and deliver high-quality software that creates measurable value for our customers and internal teams.

At Next Gear Capital, AI-assisted software development is becoming a foundational part of how we build products. As a member of the team, you'll leverage modern AI tools and development practices throughout the software development lifecycle to accelerate delivery, improve quality, and enhance collaboration. Success in this role requires both strong engineering fundamentals and the ability to thoughtfully apply AI-enabled workflows while maintaining ownership of design decisions, code quality, security, and overall solution outcomes.

You’ll have the opportunity to contribute across the full stack, participate in technical design discussions, collaborate on product strategy and delivery, and help shape how modern software engineering practices evolve within a business that is actively investing in innovation, automation, and AI-driven transformation.

• Collaborate with AI agents and tools to build, test, and deploy software across the SDLC, providing proper contextual inputs to improve AI understanding and ownership of output quality
• Contribute to prompt engineering experimentation and share tool usage insights with the team
• Engage in design and development discussions, helping the team conceptualize desired outcomes from a software engineering perspective
• Assist with feature/element estimation in terms of technical input, resources, time, and anticipated outcomes
• Develop and implement unit and system tests for integral code paths, ensuring adherence to secure coding practices at all times
• Provide technical support, including troubleshooting and enhancement, for existing and new features within application and system structures
• Use observability tools (logs, metrics, traces, dashboards) to monitor system health, diagnose issues, and validate that changes behave as expected in production
• Document processes to capture best practices, applicable methodologies, and repeatability going forward
• Update team members, manager, product owners, and other key stakeholders on status, challenges, and concerns
• Participate in code reviews, both giving and receiving feedback
• Take ownership of assigned work and drive it to completion with minimal oversight, while staying closely engaged with teammates, raising blockers early, and pitching in on shared team goals beyond your own assigned tasks

• Working Software, Every Sprint:
  Produce working software each sprint that meets the definition of done, delivers expected value, and stays within constraints defined by engineering leadership
• AI Fluency:
  Maintain effective AI-augmented workflows that measurably improve speed and quality. Actively share what works with the team
• Quality Solutions:
  Deliver maintainable, testable, and performant software that leverages existing patterns and meets client needs, with solution complexity understood well enough to produce consistent, meaningful estimates
• Craft Growth:
  Demonstrate measurable growth toward independent ownership of features and system elements
• Plan Transparency:
  Ensure changes in direction that affect time, effort, cost, or scope are surfaced to the team and above quickly
• Initiative:
  Identify opportunities for automation, improvement, or learning and act on them with minimal guidance