Lead Software Engineer Jobs in Charlotte, NC

About the role:

As a Software Engineer III at TQL, you will be a senior technical contributor responsible for designing, developing, and supporting scalable software solutions that enable our business and improve the experience of our employees, customers, and partners.

You will work as part of a collaborative, cross-functional product engineering team and take ownership of complex features and business-critical applications from design through production support. You will partner with Product, Quality Engineering, Architecture, Database Administration, Security, and other engineering teams to translate business needs into reliable, secure, and maintainable solutions.

This role requires an AI-first software development mindset. You will use approved AI-assisted engineering tools and reusable AI workflows throughout the software delivery lifecycle to accelerate discovery, design, coding, testing, documentation, troubleshooting, and operational support. You will remain accountable for the accuracy, quality, security, and maintainability of every deliverable, regardless of whether it was created with AI assistance.

What you’ll be doing:

• Design, develop, test, deploy, and maintain scalable full-stack applications across front-end and back-end technologies.
• Take end-to-end technical ownership of complex features, services, integrations, and business-critical system components.
• Translate business requirements and customer needs into technical designs, implementation options, delivery plans, and clearly defined work that can be completed by multiple team members.
• Participate in and, when appropriate, lead solution-design and architecture discussions to ensure TQL engineering patterns, security requirements, operational standards, and development practices are incorporated into solutions.
• Use approved AI development tools as an integrated part of daily engineering work, including:
  • Understanding existing applications and unfamiliar codebases.
  • Drafting and refining technical specifications.
  • Generating and refactoring code.
  • Creating unit, integration, and regression tests.
  • Reviewing pull requests and identifying potential defects or vulnerabilities.
  • Producing technical documentation.
  • Troubleshooting production and performance issues.
  • Accelerating proof-of-concept development.
• Write precise requirements, prompts, specifications, constraints, and acceptance criteria that allow AI-assisted development tools and engineering agents to produce effective, verifiable results.
• Critically evaluate AI-generated code and recommendations for correctness, security, performance, maintainability, architectural alignment, and unintended consequences before they are incorporated into production solutions.
• Apply appropriate human review and approval throughout AI-assisted delivery. TQL’s current AI-first workflow places accountability on the developer to validate generated code before opening a pull request and retains human approval for code merge and release decisions.
• Create, improve, and share reusable prompts, engineering instructions, AI workflows, agents, or other accelerators that improve team productivity and software quality.
• Select AI tools or models appropriately based on the task, expected quality, security considerations, organizational standards, and responsible use of company resources.
• Conduct and lead code reviews, promoting clean code, automated testing, secure development, and adherence to team and enterprise engineering standards.
• Collaborate with Product Owners, Product Managers, Quality Engineers, Architects, Scrum Masters, business stakeholders, and other developers throughout discovery and delivery.
• Mentor less-experienced engineers by providing technical guidance, constructive code-review feedback, pairing support, and practical coaching on the effective and responsible use of AI development tools.
• Support and improve production applications by troubleshooting complex issues, participating in operational support, identifying root causes, and recommending sustainable improvements.
• Improve the reliability, performance, security, availability, observability, and maintainability of the systems for which the team is responsible.
• Proactively identify opportunities to improve engineering practices, delivery flow, automation, and team effectiveness.
• Communicate complex technical concepts, design choices, risks, and tradeoffs clearly to both technical and nontechnical audiences.
• Use engineering and operational data to evaluate outcomes, identify improvement opportunities, and support technical recommendations.
• Stay current with developments in software engineering, cloud platforms, cybersecurity, and AI-assisted development, and responsibly introduce relevant practices to the team.

What you need:

• Bachelor’s degree in Computer Science, Information Systems, Information Technology, or a related field, or equivalent relevant professional experience.
• Typically five or more years of professional software-development experience, including meaningful ownership of production applications or services.
• Strong hands-on experience with C#, .NET, APIs, RESTful services, JSON, and SQL.
• Experience developing modern full-stack applications using front-end technologies such as Angular or React.
• Experience designing, building, testing, deploying, and supporting software in a production environment.
• Experience working within Agile or product-oriented software delivery teams.
• Strong understanding of source control, preferably Git, pull-request workflows, continuous integration, automated builds, and deployment pipelines.
• Demonstrated experience designing or contributing to business-critical systems or complex application components.
• Demonstrated ability to independently diagnose complex technical problems and recommend practical solutions.
• Experience mentoring other engineers and contributing to stronger team-level engineering practices.

AI-assisted software development skills:

• Hands-on experience using generative AI or AI coding assistants to support software development activities such as code generation, refactoring, testing, documentation, code comprehension, and debugging.
• Ability to write clear prompts, technical specifications, architectural constraints, acceptance criteria, and validation instructions for AI-assisted development.
• Ability to review and validate AI-generated code rather than accepting generated output without sufficient technical evaluation.
• Understanding of common AI limitations, including inaccurate output, insecure patterns, incomplete context, unnecessary complexity, and inconsistent results.
• Ability to protect confidential, proprietary, customer, and company information when working with AI tools.
• Experience incorporating human review, automated testing, security scanning, and observable evidence into AI-assisted delivery.
• Ability to evaluate whether an AI tool, model, agent, or automated workflow is appropriate for a particular engineering task.
• Ability to demonstrate how AI-assisted development has improved quality, delivery speed, maintainability, troubleshooting, or team effectiveness.
• Willingness to help other engineers adopt AI tools responsibly and share reusable practices across the team.

Preferred qualifications:

• Experience with Microsoft Azure or another major cloud platform.
• Experience with distributed systems, asynchronous processing, event-driven architectures, or enterprise application integration.
• Experience with automated unit, integration, API, UI, or performance testing.
• Experience with application observability, including structured logging, metrics, tracing, monitoring, and alerting.
• Experience with secure software development, vulnerability remediation, and automated security scanning.
• Experience building or integrating AI-enabled application features, large language model APIs, retrieval-augmented generation, AI agents, or model-based workflows.
• Experience developing reusable AI prompts, development instructions, agent skills, or specification-driven engineering workflows.
• Familiarity with AI governance, model risk, responsible AI practices, and the operational monitoring of AI-enabled solutions.
• Transportation, logistics, CRM, pricing, finance, warehouse-management, or other enterprise business-system experience.

Where you'll be: 200 Regency Executive Park Dr., Charlotte, NC 28217

Employment visa sponsorship is unavailable for this position. Applicants requiring employment visa sponsorship now or in the future (e.g., F-1 STEM OPT, H-1B, TN, J1 etc.) will not be considered.