Senior Software Engineer (GenAI)

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This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position. Visa Sponsorship is Available! The details are below.

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Job Title: Senior Software Engineer (GenAI) Contract Length: 6+ Months Location: CHARLOTTE NC 28202

On Site Work

Ref# 246440


Seeking a Senior Software Engineer to join a Consumer Intelligent Automation & AI engineering team focused on building enterprise-grade Agentic AI solutions. This role involves hands-on development of scalable Generative AI applications that support large-scale enterprise initiatives within a highly regulated environment.


The ideal candidate will have strong software engineering fundamentals, experience with Generative AI and large language models, cloud-native development experience, and the ability to build secure, scalable AI-powered applications integrated with enterprise systems.


Key Responsibilities

• Lead moderately complex initiatives and technical deliverables within engineering environments
• Contribute to large-scale technology planning and engineering strategy initiatives
• Design, develop, test, debug, document, and deploy applications and services
• Review and evaluate technical challenges involving engineering methodologies and technologies
• Resolve moderately complex technical issues and support evolving business requirements
• Collaborate with engineering teams, product teams, and technical leadership
• Lead projects and provide guidance to less experienced engineers
• Design, develop, and deploy AI applications using:
• Enterprise APIs
• Large language models (LLMs)
• Agent frameworks
• AI orchestration technologies
• Implement:
• Prompt engineering
• Retrieval augmented generation (RAG)
• Fine-tuning
• Agentic AI design patterns
• Integrate AI models and services into enterprise systems
• Ensure AI applications meet governance, compliance, and security requirements
• Troubleshoot application and model-related issues
• Mentor engineers on software engineering and AI development best practices
• Stay current with advancements in AI, LLMs, and agentic frameworks

Required Qualifications

• 4+ years of software engineering experience or equivalent combination of education, training, military service, or work experience
• 2+ years of experience working with:
• Generative AI
• Large language models (LLMs)
• Foundation models
• 2+ years of experience with at least one of the following:
• Google Cloud Platform (GCP)
• Microsoft Azure
• Kubernetes
• OpenShift
• 2+ years of Python development experience
• 2+ years of experience with:
• REST API development
• Docker
• Kubernetes
• 2+ years of experience using Git for:
• Branching
• Pull requests
• Collaborative development workflows

Desired Qualifications

• Understanding of cloud security principles including:
• Identity and access management
• Encryption
• Network security
• Experience working within regulated industries such as financial services
• Experience serving as a technical lead or architect
• Experience mentoring engineers
• Experience contributing to or integrating open-source AI/ML projects
• Experience integrating applications with:
• Enterprise APIs
• Data platforms
• Secure data pipelines
• Strong communication and technical documentation skills

Preferred Skills & Experience

• Power Platform experience including:
• Power Apps
• Dataverse
• UiPath or enterprise automation tools
• Experience working with:
• OpenAI
• Anthropic
• Google Gemini
• Experience with:
• Agentic frameworks
• AI workflow orchestration
• Retrieval augmented generation (RAG)
• Fine-tuning
• Structured prompting
• Experience with vector databases and retrieval systems such as:
• Elasticsearch
• OpenSearch
• Pinecone
• Weaviate
• Experience with:
• LLM evaluation
• AI observability
• Monitoring and drift detection
• AI safety assessments
• Familiarity with:
• Feature stores
• Model registries
• CI/CD pipelines for AI services
• Responsible AI and governance processes
• Experience optimizing AI application performance including:
• Prompt efficiency
• Model selection
• Caching
• Batching
• Cost management