Lead Engineer – Prep and Driver Applications

🕒 Junho 5

🔔 Pennsylvania – Remoto

🔔 Pennsylvania – Remote

💵 $125.000 - $133.000 / ano

⏰ Tempo Integral

🟠 Sênior

👷🏻‍♀️ Engenheiro

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Law School Admission Council (LSAC)

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 1947

📚 Educação

🤝 Sem Fins Lucrativos

👥 B2C

Education • Non-profit • B2C

O Law School Admission Council (LSAC) é uma organização dedicada a facilitar o processo de admissão em faculdades de direito. Oferece recursos para aspirantes a estudantes de direito, incluindo informações sobre programas de direito, preparação para o LSAT e orientações para se candidatar às faculdades de direito. O LSAC também apoia a educação jurídica por meio de pesquisas, iniciativas de diversidade e diversos fóruns para candidatos e instituições de faculdades de direito.

Descrição

• 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.

🎯 Requisitos

• 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.