Lead Engineer – Prep and Driver Applications

Role Overview

• Collaborate with partners within the company to design, configure, maintain, and promote a variety of internally
• and externally facing applications.
• Collaborate across areas to ensure application reliability and coding to architectural standards.
• Support product teams by advocating for their needs and providing constructive guidance.
• Provide the glue across dependent teams to ensure technical dependencies are planned for and addressed in a fast-paced environment.
• Connect with developers within your team to coach, inspire, and foster a continuous learning environment.
• Build and maintain scalable full-stack applications.
• Continuously monitor, test, and optimize software.
• Collaborate with software engineers, the Software Development Manager (SDM), analysts, and stakeholders to deliver solutions that meet or exceed customer expectations.
• Contribute as part of the team by leveraging continuous delivery methods and test-driven development to frequently deliver new functionality.
• Deliver high-quality code and hold the team to the same standard through code review and mentoring.
• Work to scale software to support dynamic teams in a fast-paced environment.
• Be a contributor of knowledge to the team by reviewing code, sharing experience, and listening.
• Champion and govern team-wide use of GitHub Copilot – establish prompting standards, review AI-generated code for security and quality, track productivity metrics, and coach developers on effective, responsible use of AI-assisted development.
• Drive organizational Gen-AI adoption: build and execute a structured enablement roadmap that moves the engineering organization from awareness to competency, delivering workshops lunch-and-learns, hands-on labs, and reference implementations that make AI tooling tangible and accessible for developers at all levels.
• Coach and mentor engineers on Gen-AI practices, provide 1:1 and team-level guidance on integrating AI into daily workflows including AI-assisted coding, AI-augmented code review, AI-accelerated test generation (unit, integration, regression), and effective use of AI in debugging and documentation.
• Help engineers build critical evaluation skills for vetting AI-generated output.
• Act as internal AI change agent. Identify adoption blockers, measure team AI maturity over time, gather feedback from engineers and stakeholders, and continuously iterate on enablement programs; evangelize Gen-AI success stories across the broader Technology Solutions and Platforms organization.
• Architect and implement Generative AI features using Azure OpenAI Service, OpenAI APIs, and open-source LLMs including chat interfaces, document summarization, intelligent search, and automated content generation.
• Design and maintain Retrieval-Augmented Generation (RAG) pipelines integrating vector databases (e.g., Azure AI Search, Pinecone, pgvector) with enterprise data sources to ground model outputs in authoritative content.
• Lead prompt engineering efforts; craft, version, evaluate, and iteratively refine system prompts, few-shot examples, and chain-of-thought strategies to maximize accuracy and safety.
• Establish and enforce responsible AI practices, bias evaluation, content filtering, PII redaction, audit logging, and compliance with LSAC data governance standards for all AI-powered features.

Requirements

• 5–10 years of experience in full stack software engineering
• B.A. or B.S. degree in Computer Science, Software Engineering, or related field
• Master's degree preferred.
• Azure certifications (e.g., AZ-204, AZ-400, AZ-305) preferred.
• Azure AI certifications – AI-102 (Azure AI Engineer Associate) and/or Microsoft certified, Azure OpenAI certification or equivalent demonstrated proficiency preferred.
• Coursework, certifications, or verifiable project experience in machine learning fundamentals, natural language processing, or applied AI/ML (e.g., DeepLearning.AI, fast.ai, Coursera ML Specialization) preferred.
• Demonstrated track record of driving Generative AI adoption across an engineering team or organization.
• GitHub Copilot experience required.
• AI coaching and mentoring experience required.

Tech Stack

• Azure