.NET Software Developer

<p>Title: Sr Specialist - Software Development &amp; Engineering</p><p>Duration: 6 Months. This is a contract to hire role.</p><p>Location: Southlake, TX - Austin, TX could be a backup | In office four days per week</p><p>The candidate will work with a team of .NET engineers and be responsible for developing and improving investment in lifecycle solutions in Risk Solutions. Ideal candidates enjoy fast-paced environments, thrive under ambiguity, adopt change passionately, and demonstrate practical knowledge of AI-assisted development, AI application concepts, and responsible use of generative AI in software delivery.</p><p>This role is responsible for application development in an enterprise architecture environment within the .NET framework using C#. You will work within and across Agile teams to design, develop, test, implement, and support technical solutions across a full stack of development tools, technologies, and approved AI developer productivity capabilities to ensure on-time, high-quality delivery of software products.</p><h3>Key Responsibilities</h3><ul><li>Responsible for the design, development, deployment, and maintenance of web UI and REST APIs.</li><li>Troubleshoot and support applications in production in case of issues.</li><li>Identify ways to improve technology, processes, and performance.</li><li>Identify opportunities to apply approved AI tools and AI-assisted engineering practices to improve development velocity, code maintainability, testing efficiency, and documentation quality.</li><li>Participate in design, code, AI-assisted code validation, and technical design reviews.</li><li>Build solutions that significantly impact company growth.</li><li>Participate in an Agile scrum-based software development environment.</li><li>Work closely with internal and external team members to decompose requirements, design software, and prioritize tasks.</li><li>Collaborate with product, architecture, security, and engineering partners to evaluate AI-enabled application patterns, automation opportunities, and responsible AI considerations where appropriate.</li><li>Meet periodically with onsite and offshore developers to review and improve code quality, requirements specifications, and design methodologies.</li><li>Troulbleshoot, debug, and improve existing integrations and software.</li><li>Actively participate in team meetings to ensure team deliverables are met.</li><li>Provide hands-on development, AI-assisted engineering guidance, and mentoring as necessary for other members of the development team.</li><li>Create project artifacts such as technical specifications, AI usage notes, solution design documentation, and metrics reports.</li><li>Identify technology risks early and establish mitigation plans.</li><li>Appy AI-assisted development practices to improve engineering productivity, code quality, testing, documentation, and solution delivery.</li></ul><h3>Required Qualifications</h3><ul><li>Solid background in application development; minimum 5 years of experience.</li><li>Demonstrated ability to apply .Net development tools and techniques across coding, debugging, refactoring, test creation, documentation, and code review workflows.</li><li>Proficient building client/server-side applications using .NET.</li><li>Strong understanding of relational and SQL database concepts; minimum 3-5 years of experience and proficiency in SQL Server.</li><li>Familiar with creating REST API integrations; minimum 1-3 years of experience.</li><li>Familiarity with AI application development patterns such as prompt engineering, model/API integration, retrieval-augmented workflows, intelligent automation, and human oversight of AI-generated outputs.</li><li>Proven history of debugging and troubleshooting full-stack applications.</li><li>Understanding of large dataset manipulation, movement techniques, and related challenges.</li><li>Understanding of Agile software development methodologies, concepts, and procedures.</li><li>Comfortable with tools including Jira, GitHub, or similar platforms.</li><li>Comfortable using approved AI developer productivity tools, including AI coding assistants, prompt-based code exploration, and AI-supported documentation or test generation while applying sound engineering judgment.</li><li>UI development experience with a single-page application framework.</li><li>Experience with native cloud architecture or PCF equivalent.</li><li>Comfortable with Git source code management, branching, and code merges.</li><li>Comfortable in a fast-paced, customer-focused Agile environment that continually embraces change.</li><li>Good problem-solving skills with a design-first mindset.</li><li>Working knowledge of AI application development concepts, including prompt engineering, AI-assisted coding tools, model integration patterns, responsible AI practices, and practical use of generative AI in software delivery.</li></ul><h3>Preferred Qualifications</h3><ul><li>Experience in financial technology domains and Angular or single-page application development.* Experience with SSIS or other data load/ETL tools.</li><li>Experience developing or integrating AI-enabled applications, automation capabilities, intelligent workflows, or enterprise productivity solutions using modern AI platforms and APIs.</li><li>Experience designing secure and scalable AI-enabled features, including integration with enterprise APIs, data pipelines, cloud services, observability, and quality controls.</li><li>Enterprise system production support, DevOps, and release management experience.</li><li>Continuous integration experience with Bamboo, Jenkins, or other CI/CD tools.</li><li>Prior experience building financial services applications or platforms.</li><li>Experience in enterprise public cloud environments such as GCP, AWS, Azure, or equivalent platforms.</li><li>Experience with Bamboo for CI/CD deployment automation and Python for service automation.</li><li>Cloud-native design pattern experience.</li><li>Development experience focused on performance, application security, and other non-functional requirements.</li><li>Knowledge of responsible AI practices, AI output validation, data privacy, application security, model risk awareness, and governance considerations for enterprise AI solutions.</li><li>Experience with Google Cloud Platform and familiarity with Docker/containerization.</li><li>Knowledge of cloud concepts such as cloud deployments, microservice infrastructure, cloud configuration, and Pivotal Cloud Foundry.</li><li>BS/BA in Computer Science or an equivalent discipline.</li></ul><br />#J-18808-Ljbffr