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Law School Admission Council

Operates LSAT testing and CAS services

Engineer Lead with Generative AI experience

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$125k - $133k

About the Job

Requirements

  • Strong written and verbal communication skills, with experience using Microsoft Teams.
  • A strong sense of accountability for individual and team objectives.
  • Excellent time management, prioritization, attention to detail, and organizational skills.
  • Ability to listen to stakeholders and form solutions.
  • Proven ability as a servant leader.
  • Experience with relational and unstructured data repositories, including stored procedures, scripts, Cosmos DB, SQL, and Oracle.
  • Experience with web and cross-platform technologies including Web Services, React JS, Microsoft Visual Basic, and C# .NET frameworks (Web Forms, Windows Forms, .NET Web API, Entity Framework 6.4+, MVC, and SPA).
  • Experience with a variety of object-oriented languages.
  • Experience with Git, code management methods, CI/CD pipelines, and Azure DevOps.
  • Familiarity with RESTful or web APIs.
  • Familiarity with Web Content Accessibility Guidelines (WCAG) 2.1 and ARIA standards.
  • Knowledge of the Azure technology stack, including Azure Functions, Azure Data Factory, Azure Storage Account, Azure Key Vault, Azure Cosmos DB, Service Bus, Azure App Service, Azure VMs, and Azure Table Storage.
  • Knowledge of modern development practices and the development lifecycle, with experience using Scrum, Kanban, Lean, or other agile methodologies.
  • Five to ten years of experience in full-stack software engineering.
  • A B.A. or B.S. degree in Computer Science, Software Engineering, or a related field.
  • Generative AI change leadership is required, including a demonstrated track record of driving adoption across an engineering team or organization, designing enablement programs, communicating AI tools' value to skeptical stakeholders, measuring adoption, and iterating based on feedback.
  • AI coaching and mentoring experience is required, including uplifting peers and direct reports on AI-assisted coding, prompt design, AI-augmented unit, integration, and regression test generation, AI-assisted debugging, and responsible use of AI-generated code; ability to assess AI maturity and tailor coaching accordingly.
  • Production-level GitHub Copilot proficiency in VS Code or JetBrains IDEs, including writing inline prompts, using Copilot Chat, enforcing review standards for AI-generated output, and configuring and managing Copilot at the organization or repository level through GitHub Enterprise settings.
  • Ability to design structured prompts, implement few-shot and chain-of-thought patterns, and use evaluation frameworks such as Azure AI Evaluation, Promptflow, or Ragas to measure quality and regression.
  • Understanding of responsible AI and AI governance, including content safety controls, PII handling in LLM contexts, model fairness, explainability, and Microsoft Responsible AI principles.

Responsibilities

  • Collaborate with company partners to design, configure, maintain, and promote internally and externally facing applications.
  • Collaborate across areas to ensure application reliability and adherence to architectural standards.
  • Support product teams by advocating for their needs and providing constructive guidance.
  • Coordinate across dependent teams to ensure technical dependencies are planned for and addressed.
  • Coach, inspire, and foster continuous learning among team developers.
  • Build and maintain scalable full-stack applications.
  • Continuously monitor, test, and optimize software.
  • Collaborate with software engineers, the Software Development Manager, analysts, and stakeholders to deliver solutions that meet or exceed customer expectations.
  • Use continuous delivery methods and test-driven development to deliver new functionality frequently.
  • Deliver high-quality code and uphold the same standard through code review and mentoring.
  • Scale software to support dynamic teams.
  • Review code, share experience, and contribute knowledge to the team.
  • Champion and govern team-wide GitHub Copilot use by establishing prompting standards, reviewing AI-generated code for security and quality, tracking productivity metrics, and coaching developers in effective and responsible use.
  • Drive organizational Generative AI adoption by building and executing an enablement roadmap, and delivering workshops, lunch-and-learns, hands-on labs, and reference implementations.
  • Coach and mentor engineers on integrating Generative AI into daily workflows, including AI-assisted coding, AI-augmented code review, AI-accelerated test generation, debugging, and documentation; help engineers critically evaluate AI-generated output.
  • Identify AI adoption blockers, measure team AI maturity, gather feedback, iterate on enablement programs, and share Generative AI success stories across the 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 pipelines integrating vector databases such as Azure AI Search, Pinecone, and pgvector with enterprise data sources.
  • Lead prompt engineering by crafting, versioning, evaluating, and refining 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 data governance standards.

Desired Qualifications

  • Experience with Selenium or comparable automated testing frameworks.
  • Experience with agentic AI patterns such as AutoGen, Azure AI Agent Search, tool-calling, and multi-agent orchestration.
  • Familiarity with MLOps/LLMOps practices, fine-tuning pipelines, model versioning, deployment monitoring, and drift detection.
  • A master's degree.
  • Azure certifications such as AZ-204, AZ-400, or AZ-305.
  • Azure AI certifications such as AI-102, Azure OpenAI certification, or equivalent demonstrated proficiency.
  • Coursework, certifications, or verifiable project experience in machine learning fundamentals, natural language processing, or applied AI/ML, such as DeepLearning.AI, fast.ai, or Coursera ML Specialization.

About the Company

Law School Admission Council

Operates LSAT testing and CAS services

LSAC is a nonprofit that manages the law school admission process in North America, primarily through the LSAT and the Credential Assembly Service (CAS). The LSAT is a standardized exam that tests reading, analytical, and logical reasoning and is required by ABA-approved law schools. The CAS lets applicants send transcripts and letters of recommendation to LSAC once, after which LSAC compiles them with the LSAT score into a report sent to all law schools the applicant applies to. LSAC earns money from service fees for the LSAT and CAS, and also conducts data collection and research on admissions trends. Its goal is to promote fair, data-informed access to legal education for over 100,000 annual test-takers and member law schools in the US, Canada, and Australia.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
1947

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