Technology and Data - Software Engineer 4 - Contingent

Job ID: 26-12553Location: CHARLOTTE, NCContact: Vishal JaiswalContact Email: View email address on click.appcast.io Phone: 2013865400Company: MindlanceIn this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Software Engineering. Review and analyze complex multi-faceted, larger scale or longer-term Software Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. ---------------------------------------------------------------------------------------------------------------------------------------- • Partner with business stakeholders, product owners, and engineering teams to understand business problems, identify AI-enabled opportunities, and define end-to-end technical solutions. • Design, prototype, and deliver AI-driven workflows, agents, copilots, and automations using large language models (LLMs) and enterprise AI services. • Integrate AI capabilities with enterprise platforms and systems (e.g., ServiceNow, Salesforce, data platforms, internal services) using secure APIs and orchestration patterns. • Rapidly iterate on prototypes and transition them into production-ready solutions that meet enterprise standards for reliability, scalability, and supportability. • Act as a technical bridge between business, product, data, security, and engineering teams to ensure solutions are usable, compliant, and aligned with business objectives. • Lead solution architecture and design activities, including: o Prompt engineering and AI workflow design o API integration and service orchestration o Enterprise knowledge and data integration o Security, privacy, risk, and governance considerations • Own solutions across the full lifecycle—from concept and proof of value through production deployment and continuous improvement. • Apply and promote best practices for responsible AI, including model risk management, data protection, and compliance with enterprise and regulatory requirements. • Contribute to the development of reusable patterns, standards, and guidance to support scalable AI adoption across the enterprise. EEO: “Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”