Principal Engineer, Applied AI

National Debt Relief, LLC.

1d•Remote

About The Position

National Debt Relief (NDR) is seeking highly skilled and technically curious Principal Applied AI Engineers to join our growing Data & AI organization. Reporting to the Director of Applied AI, these roles will be foundational members of the Applied AI team responsible for the hands-on implementation of enterprise-grade Generative AI (GenAI) solutions. This is an exciting opportunity to build and deploy real-world, production-ready AI applications that transform client experiences, optimize internal operations, and unlock intelligent automation at scale. As a Principal Applied AI Engineer, you will own the technical execution of GenAI initiatives — from prototyping to deployment. You’ll work closely with internal product, data, engineering, and digital teams, as well as external vendors, to deliver practical, scalable and robust solutions powered by LLMs, RAG pipelines, and conversational AI. Your work will span chatbot development, document processing, summarization, voice AI, and AI-driven analytics. You will define architectural patterns, establish best practices, lead projects, influence roadmaps and provide mentoring to other engineers. This role is ideal for AI practitioners who have experience deploying production-grade GenAI solutions and want to continue building in a fast-moving, applied environment.

Requirements

Bachelor’s degree in data science, Computer Science, Statistics, or a related field required.
8 years of experience in machine learning, NLP, AI engineering, software engineering, and data engineering with recent focus on LLMs / Generative AI.
Proven, hands-on experience building and deploying production-grade AI chatbots in the past 2 years.
Expert-level Python programming skills, including experience with modern ML and GenAI libraries (e.g., LangChain, Transformers, OpenAI, Hugging Face).
Proficiency in working with vector databases (e.g., FAISS, Pinecone, Chroma, Weaviate) and building RAG pipelines.
Experience with prompt engineering, model tuning, API orchestration, and LLM evaluation strategies.
Solid SQL skills and understanding of how to work with data stored in platforms like Snowflake.
Comfortable working in fast-paced, collaborative environments with product managers, engineers, and vendors.
Strong communication skills with the ability to explain complex AI behavior and performance to non-technical stakeholders.
Ability to foster a culture of collaboration, continuous improvement, and innovation.
Computer competency and ability to work with a computer.
Prioritize multiple tasks and projects simultaneously.
Exceptional written and verbal communication skills.
Punctuality expected, ready to report to work on a consistent basis.
Attain and maintain high performance expectations on a monthly basis.
Work in a fast-paced, high-volume setting.
Use and navigate multiple computer systems with exceptional multi-tasking skills.
Remain calm and professional during difficult discussions.
Take constructive feedback.
Available for full-time position.

Nice To Haves

Experience in financial services or a related industry.
Experience deploying voice AI or conversational AI agents in telephony environments.
Familiarity with Snowflake, dbt, and data pipelines used in support of AI solutions.
Experience working with or integrating Salesforce data and workflows.
Exposure to GenAI use cases including document understanding (OCR/NLP), summarization, or personalized insights.
Prior experience supporting regulated environments or customer service applications.

Responsibilities

Design, prototype, and deploy Generative AI solutions across NDR’s client-facing and internal platforms.
Build and optimize applications using large language models (LLMs), vector databases, prompt engineering, and Retrieval-Augmented Generation (RAG) pipelines.
Own hands-on development of AI-powered chatbots using modern conversational AI frameworks, ensuring production-grade performance, scalability, and compliance.
Lead development of AI agents for both digital and voice channels, supporting real-time interactions with clients and internal users.
Work with external vendors to evaluate GenAI platforms and APIs, integrate off-the-shelf solutions, and drive production rollouts.
Build proof-of-concept (POC) applications to evaluate emerging use cases in document classification, summarization, AI-powered knowledge assistants, and more.
Optimize prompt structures, parameter tuning, and model usage to improve cost-effectiveness and accuracy of deployed AI solutions.
Partner with the ML/AI Ops Engineer to ensure robust data pipelines, deployments, and observability for GenAI applications.
Work closely with the Senior Generative AI Product Manager to align technical implementation with user needs, timelines, and business priorities.
Lead architectural design discussions with digital, product, and engineering teams to align AI integration across the enterprise.
Drive technical execution and architectural alignment across multiple teams and stakeholders on high-impact AI initiatives.
Tackle ambiguous or technically complex problems and provide guidance on solution design and tradeoffs.