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# Forward Deployment Engineer (Quantitative Analytics Specialist 4 - Contingent)

- **Company:** Everforth Apex
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $166,400.0 - $180,960.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Information Engineering, Rapid Prototyping Process, SQL Databases, Unstructured Data, Google Cloud, Large Language Models, Prompt Engineering, Build Management, Containerization, Kubernetes, Docker
- **Published:** June 16, 2026
- **Apply:** https://www.dice.com/job-detail/ec7161ef-7904-4a53-ac5a-74dd894e18f8

## About the Role

* 5+ years of Quantitative Analytics, Applied AI/ML, or equivalent experience
 * Strong experience with GenAI (LLMs, RAG pipelines, prompt engineering, agentic frameworks)
 * Experience with API integration, cloud platforms (AWS/Azure/Google Cloud Platform), and CI/CD/deploymentPlusses:

 * Prior financial services experience (preferred but not required)
 * Experience with containerization (Docker/Kubernetes)
 * Strong data engineering skills (SQL, pipelines, structured/unstructured data)

## Description

In this contingent resource assignment, you will consult on complex initiatives with broad impact and large-scale planning for Quantitative Analytics. You will review and analyze complex, multi-faceted challenges requiring deep evaluation of multiple factors, including ambiguous or unprecedented situations. You will contribute to resolving complex issues, leveraging a strong understanding of policies, procedures, and compliance requirements, while collaborating strategically with business and technical stakeholders.
Day-to-Day Responsibilities:

 * Partner directly with Enterprise AI teams and business stakeholders to translate real-world requirements into production-grade AI solutions
 * Own full lifecycle delivery including rapid prototyping, development, deployment, and production hardening
 * Design and build AI/ML and GenAI solutions (LLMs, RAG pipelines, prompt engineering, agent-based workflows)
 * Integrate AI applications with enterprise APIs, data sources, and internal systems
 * Develop and deploy solutions using cloud platforms (AWS, Azure, Google Cloud Platform) and CI/CD pipelines
 * Work with structured and unstructured data to support AI-driven use cases
 * Collaborate cross-functionally to scope, iterate, and refine solutions quickly
 * Ensure solutions meet security, regulatory, and compliance standards within a financial services environment
 * Communicate technical concepts clearly to both technical and non-technical stakeholders


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