GenAI Software/Capabilities Engineer

Motion Recruitment

Minneapolis (MN)

Hybrid

USD 112,963 - 123,984

Full time

14 days+

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Job summary

A well-known Financial Services Company is seeking a GenAI Engineer to lead Agile development teams and create innovative technology solutions. The ideal candidate will have over 10 years of software engineering experience, with strong skills in C# and Python, as well as expertise in integrating Large Language Models. This full-time position offers a hybrid work environment in Iselin, NJ.

Qualifications

10+ years of software engineering experience.
5+ years using C# (.NET Core) and Python focused on backend systems.
Experience integrating large language models (LLMs) into web applications.
Advanced troubleshooting skills.

Responsibilities

Lead an Agile development team in creating technology frameworks.
Provide mentorship and technical leadership to software engineers.
Develop highly interactive user interfaces using the React framework.
Architect and build secure APIs for front-end applications.

Skills

C# (.NET Core)

Python

Agile methodologies

Large Language Models (LLMs)

Prompt engineering

Tools

uDeploy (Urbancode Deploy)

GitHub Actions

Jenkins

Job description

Overview

Outstanding long-term (multi-year) contract opportunity! A well-known Financial Services Company is looking for a GenAI Engineer in Iselin, NJ (Hybrid).

Base pay range

$82.00/hr - $90.00/hr

What You Will Be Doing

Lead an Agile development team in the creation and implementation of new and existing technology frameworks, feature enhancements, applications redesigns efforts, componentized applications, micro-services, information security, database, and cloud or web technologies

Technical Leadership & Mentorship: Lead a team of software engineers, providing technical guidance, code reviews, and mentorship to ensure high-quality code and professional growth.

Architect and build scalable, robust, and performant applications, including:
- Develop complex and highly interactive user interfaces using the React UI framework. Focus on creating a seamless and responsive user experience for self-service portal applications.
- Design, develop, and maintain secure and scalable APIs to support front-end applications and integrate with various services.
- Leverage your experience with Large Language Models (LLMs) to integrate AI capabilities directly into applications, including working with LLM APIs, prompt engineering, and understanding the challenges and opportunities of AI-enabled features.
- Self-Service Portal Development: Lead the end-to-end development of self-service portal-type applications, focusing on user autonomy, intuitive workflows, and streamlined user experience.
- Agile Development & User-Centered Design: Actively participate in and lead an Agile development environment (e.g., Scrum, Kanban).

Qualifications

The ideal candidate will have proven experience in full-stack software engineering with a strong grasp of modern development frameworks and tools. Demonstrated leadership in both technical execution and team collaboration and deep understanding of agile methodologies and a track record of delivering high-impact solutions in iterative cycles, and a passion for building seamless, intelligent user experiences powered by AI.

Required Skills & Experience

10+ years of software engineering experience

5+ years of software development experience using C# (.NET Core) and Python, with a strong focus on backend systems and service-oriented architecture

4+ years of experience in one or a combination of the following Enterprise Pipeline Tools: uDeploy (Urbancode Deploy), GitHub Actions, Harness, Jenkins

2+ years of experience integrating large language models (LLMs) into web applications. Proficient in providing contextual grounding to LLMs using techniques such as Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and similar approaches.

Skilled in prompt engineering to optimize LLM outputs for diverse use cases, including task-specific prompting, chain-of-thought reasoning, and few-shot examples to enhance model accuracy, relevance, and reliability.