Associate AI Engineer

The AI Engineering team within the Enterprise Data and Information Management (EDIM) group develops and deploys advanced AI productivity solutions for Navy Federal Credit Union. This role focuses on designing and implementing scalable, secure, and efficient AI systems using state-of-the-art Large Language Models (LLMs) and modern cloud frameworks. The engineer collaborates with Enterprise Technology Services (ETS) and business units to deliver modular, reusable AI components that address complex business challenges.

Strong problem-solving, communication, analytical, and leadership skills are essential for success in this position.

• As a member of the AI Center for Enablement (C4E), contribute to platform, engineering, and operations to drive the adoption and utilization of AI capabilities, fostering technological innovation and improving member experience through AI capabilities.
• Implement AI engineering solutions while adhering to established governance, validation, safety, and transparency guidelines.
• Develop AI capabilities using LLM models and evaluate outcomes to ensure accuracy, reduce hallucinations, and assure compliance.
• Build and manage data pipelines for structured and unstructured data ingestion.
• Implement Retrieval-Augmented Generation (RAG) and other techniques to improve model accuracy and reduce hallucinations.
• Ensure compliance with AI governance, security, and ethical standards.
• Optimize application performance and scalability using cloud-native solutions.
• Participate in Agile development cycles and CI/CD processes for rapid deployment.
• Follow established AI standards and assist with model documentation and registration activities in the Model Catalog, in accordance with security and regulatory guidelines.
• Contribute to documentation and implementation of approved AI/ML roadmaps and technical plans.
• Support developer productivity initiatives by leveraging AI-assisted coding tools and contribute to AI-driven solutions.
• Deliver core engineering skills related to LLMs, prompt engineering, and applications delivery.
• Collaborate with senior team members to support initiatives that advance NFCU’s AI Center for Enablement capabilities.

• Bachelor’s degree in AI Engineering, Computer Science, Data Science, or related technical field, or the equivalent combination of education, training and experience.
• 1-2 years of experience in building AI solutions, including AI agents and chatbots, using industry-leading platforms (e.g., Azure AI Foundry).
• Experience delivering solutions using Python, SQL and No
  
  SQL capabilities.
• Experience with front-end and back-end development using frameworks like React, Angular, and Node.js, Django, or Flask respectively for creating user interfaces and services.
• Experience with API development and integration building RESTful APIs for connecting AI models to applications
• Experience with LLMs (Large Language Models), prompt engineering, and fine-tuning.
• Experience with Natural Language Processing (NLP) using tokenization, embeddings, and conversational AI techniques.
• Experience with using Retrieval-Augmented Generation (RAG) for grounding models in factual data and reducing hallucinations.
• Experience in building data pipelines and data preprocessing for structured and unstructured data sets using platforms such as Databricks or similar.
• Experience in using Vector Databases & Graph Databases for semantic search and recommendation systems.
• Enable Model Governance implementing transparency, bias detection, and compliance measures.
• Implement security controls ensuring safe deployment of AI models and protect sensitive data.
• Strong understanding of CI/CD, Git, and Agile methodologies.
• Experience using AI-assisted coding tools (e.g. Git Hub Copilot) as part of development workflows.
• Strong documentation, communication and presentation skills to explain designs and solutions to business and technical stakeholders.
• Demonstrated understanding of software engineering fundamentals, including data structures, debugging, unit testing, and writing maintainable, well-documented code.
• Familiarity with dependency management, logging, error handling, differences between…