Lead Engineer – Prep and Driver Applications

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Work alongside internal partners to design, configure, maintain, and promote a range of applications that serve both internal and external users.

• Collaborate across different teams to guarantee application reliability and adherence to architectural standards in coding.

• Advocate for the needs of product teams and provide constructive guidance to support their objectives.

• Act as a unifying force among dependent teams to ensure that technical dependencies are efficiently planned for and resolved in a fast-paced environment.

• Engage with developers in your team to mentor, motivate, and cultivate a culture of continuous learning.

• Develop and sustain scalable full-stack applications.

• Continuously assess, test, and optimize software performance.

• Partner with software engineers, the Software Development Manager (SDM), analysts, and stakeholders to deliver solutions that meet or surpass customer expectations.

• Contribute to the team by utilizing continuous delivery methods and test-driven development to regularly introduce new functionalities.

• Produce high-quality code and uphold the same standards within the team through code reviews and mentorship.

• Work on scaling software to accommodate dynamic teams in a rapid environment.

• Share knowledge with the team by reviewing code, sharing experiences, and actively listening.

• Advocate and oversee the team-wide implementation of GitHub Copilot – establish prompting standards, review AI-generated code for security and quality, monitor productivity metrics, and guide developers in the effective, responsible use of AI-assisted development.

• Lead the organizational adoption of Generative AI: create and implement a structured enablement roadmap that transitions the engineering organization from awareness to competency, delivering workshops, lunch-and-learns, hands-on labs, and reference implementations that make AI tools tangible and accessible for developers at every level.

• Coach and mentor engineers on best practices for Generative AI, providing individual and team-level guidance on integrating AI into daily workflows, including AI-assisted coding, AI-enhanced code review, AI-accelerated test generation (unit, integration, regression), and effective utilization of AI in debugging and documentation.

• Assist engineers in developing critical evaluation skills for assessing AI-generated outputs.

• Serve as an internal change agent for AI adoption by identifying barriers, measuring team AI maturity over time, gathering feedback from engineers and stakeholders, and continually refining enablement initiatives; promote success stories in Generative AI across the broader Technology Solutions and Platforms organization.

• Design and implement Generative AI features using Azure OpenAI Service, OpenAI APIs, and open-source large language models (LLMs), including chat interfaces, document summarization, intelligent search, and automated content generation.

• Create and manage Retrieval-Augmented Generation (RAG) pipelines that integrate vector databases (such as Azure AI Search, Pinecone, pgvector) with enterprise data sources to ensure model outputs are grounded in authoritative content.

• Lead efforts in prompt engineering; craft, version, evaluate, and iteratively refine system prompts, few-shot examples, and chain-of-thought strategies to enhance accuracy and safety.

• Establish and uphold responsible AI practices, including bias evaluation, content filtering, PII redaction, audit logging, and compliance with LSAC data governance standards for all AI-driven features.

⛳️ Requirements

• 5–10 years of experience in full-stack software engineering.

• B.A. or B.S. degree in Computer Science, Software Engineering, or a related field.

• A Master's degree is preferred.

• 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.

• 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) is preferred.

• Proven track record of promoting Generative AI adoption within an engineering team or organization.

• Experience with GitHub Copilot is required.

• Experience in AI coaching and mentoring is required.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements to maintain work-life balance.

• Access to cutting-edge technology and tools.

• Collaborative and inclusive work environment.