Amazon Web Services (AWS), Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Best Practices, Cloud Computing, Communication Skills, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Cross-Functional, Customer Relations, Data Management, Docker, Enterprise Protection, Financial Services, Identify Issues, Microsoft Windows Azure, Modeling Languages, Problem Solving Skills, Product Lifecycle, Proof of Concept, REST (Representational State Transfer), Rapid Prototyping, Regulatory Compliance, SQL (Structured Query Language), Structured Data, Team Player, Unstructured Data
Forward Deployment Engineer (AI/GenAI)
Job Type: Contract
Location: Charlotte, NC | Bay Area, CA | Dallas, TX (Hybrid/Onsite as required)
Max Pay Rate:$82/hr
Job Overview
We are seeking an experienced Forward Deployment Engineer to join a leading Enterprise AI team. In this role, you will work directly with business stakeholders and engineering teams to transform real-world business challenges into production-ready AI solutions.
This is a highly collaborative, customer-facing role where you'll own the complete solution lifecycle—from rapid prototyping and proof of concepts to deployment, integration, and production hardening. You'll serve as the technical bridge between AI platforms and the teams that rely on them to drive business outcomes.
Responsibilities
- Partner with business stakeholders to understand complex requirements and design AI-driven solutions.
- Build, prototype, and deploy enterprise-grade Generative AI applications.
- Develop solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agentic AI frameworks.
- Integrate AI applications with enterprise systems, APIs, and data platforms.
- Deploy and maintain AI solutions using modern cloud and container technologies.
- Collaborate with cross-functional teams throughout the development lifecycle.
- Translate technical concepts into business-friendly solutions and recommendations.
- Ensure solutions align with enterprise security, governance, and compliance standards.
- Support continuous improvement through rapid iteration and stakeholder feedback.
Required Qualifications
- 6–10 years of professional software engineering or AI/ML experience.
- Hands-on experience building applications using:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Agentic AI frameworks
- Experience integrating applications using REST APIs and enterprise services.
- Working knowledge of cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Strong SQL skills and understanding of data pipelines and structured/unstructured data.
- Excellent analytical, troubleshooting, and problem-solving skills.
- Strong communication and stakeholder management experience.
- Ability to thrive in a fast-paced, ambiguous environment while delivering production-quality solutions.
Preferred Qualifications
- Experience within the financial services industry.
- Exposure to regulated enterprise environments.
- Previous experience supporting Enterprise AI initiatives.
- Familiarity with security, governance, and compliance best practices for AI solutions