Senior Software Engineer (contract)

Title: Senior Software Engineer

Location: Charlotte, NC

Duration: 6 months

Work Engagement: W2

Work Schedule: Hybrid 3 days in office/2 days remote

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables. Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Software Engineering. Required Qualifications: Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

• Lead moderately complex initiatives and deliverables within technical engineering environments
• Contribute to large scale planning of strategies across Consumer Technology
• Design, code, test, debug, and document applications and services including upgrades and deployments
• Review technical challenges that require in depth evaluation of technologies, procedures, and engineering approaches
• Resolve moderately complex issues while guiding teams to meet existing and emerging business needs
• Collaborate with peers, colleagues, and mid level managers to resolve technical challenges and meet project goals
• Lead projects and act as an escalation point, providing direction to less experienced engineers
• Design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies
• Implement prompt engineering, retrieval augmented generation, fine tuning, and agentic design patterns
• Integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards
• Troubleshoot complex application and model related issues and contribute to the continuous improvement of AI systems
• Assist and mentor engineers in advanced software development and AI engineering practices
• Stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems

• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.
• Software engineering experience or equivalent through a combination of work experience, training, military service, or education
• Experience working with Generative AI, large language models, or foundation models
• Experience with either GCP, Azure, Kubernetes, or OpenShift
• Experience with Python
• Experience with REST API development and containerization technologies such as Docker and Kubernetes
• Experience using Git for source code version control, including branching, pull requests, and collaborative development workflows

• Understanding of cloud security principles including identity and access management, encryption, and network security in public or hybrid cloud environments
• Experience working in highly regulated industries such as financial services
• Experience as a technical lead or architect, including mentoring senior engineers
• Experience integrating or contributing to open-source AI or ML projects
• Experience integrating applications with enterprise data platforms, APIs, and secure data pipelines
• Strong communication and documentation skills to collaborate across engineering, product, and oversight teams

• Experience with Power Platform, including Power Apps and Dataverse
• Experience with UiPath or other enterprise automation tools
• Experience with LLM development using OpenAI, Anthropic, or Google Gemini models
• Experience with agentic frameworks and AI workflow orchestration
• Experience designing applications that incorporate retrieval augmented generation, fine tuning, and structured prompting
• Experience with vector databases and retrieval systems such as Elasticsearch, OpenSearch, Pinecone, or Weaviate
• Experience with LLM evaluation, observability, and monitoring including latency, cost, accuracy, grounding, drift detection, and safety assessments
• Familiarity with ML lifecycle tools and processes such as feature stores, model registries, and CI or CD pipelines for AI services
• Familiarity with responsible AI principles, compliance, and governance processes related to AI systems in regulated environments
• Experience optimizing AI application performance including prompt efficiency, model selection, caching, batching, and cost management