Senior Software Development Engineer

Gibson Dunn is a leading global law firm, advising clients on significant transactions and disputes. Our exceptional teams craft and deploy creative legal strategies that are meticulously tailored to every matter, however complex or high-stakes. The firm’s work is distinguished by a unique combination of precision and vision.

Based in New York or Washington D.C., the Senior Software Development Engineer will be responsible for designing, architecting, building, and leading the delivery of enterprise applications and shared platform capabilities across the firm. As part of the firm’s strategic investment in artificial intelligence, this role will develop next-generation applications that enable attorneys and business professionals to work more efficiently, uncover insights faster, and deliver exceptional client service.

The Senior Software Development Engineer will serve as a technical leader, partnering closely with the AI Platform and Data Engineering teams, product owners, attorneys, and business stakeholders to translate complex business needs into scalable software solutions. The role will lead initiatives from rapid prototype through production implementation, with a particular focus on AI-enabled products and applications, agentic workflows, enterprise integrations, and modern software engineering practices.

Primary applications and platforms include:

Microsoft Azure, including Azure App Services, Azure Functions, Azure API Management, Azure SQL, Cosmos DB, and Storage Accounts

C#, .NET, Python, JavaScript, and TypeScript

React, Angular, or similar front end technologies

Large language models, retrieval augmented generation, and AI enabled applications

Agent orchestration frameworks, including LangGraph and Semantic Kernel

Model Context Protocol

Vector and hybrid search technologies

Docker and Kubernetes

Terraform and Bicep

Git based source control and CI/CD platforms

Data pipeline, machine learning, and MLOps tooling

AWS services, including SageMaker, Glue, Athena, Lambda, ECS, and S3

Responsibilities include:

Application Development & Architecture

Designing, developing, and maintaining enterprise-grade applications, APIs, services, and shared platform capabilities.

Developing AI-enabled solutions that integrate the firm’s proprietary large language models, services, retrieval capabilities, and intelligent agent frameworks into legal and business workflows.

Leading the technical architecture and end-to-end delivery of complex software initiatives from rapid prototyping and proof of concept through production implementation.

Defining technical strategies and architecture patterns that balance scalability, maintainability, security, reliability, and performance.

Translating complex legal and business workflows into scalable technical solutions, including determining where AI-enabled or agent-assisted solutions can provide meaningful value.

Automating manual and email-driven processes through data-integrated workflows and intelligent decision support.

Evaluating emerging technologies and recommending adoption where appropriate.

AI & Agentic Workflow Engineering

Designing and building agentic workflows that plan, invoke tools, and execute multi-step legal and business processes.

Developing tools and Model Context Protocol interfaces that securely connect AI agents with firm systems and data.

Building orchestration capabilities including state management, retries, checkpointing, human review, approvals, and safe recovery for long-running workflows.

Develop, deploy, and maintain AI-powered applications, large language model (LLM) solutions, retrieval-augmented generation (RAG) architectures, intelligent agents, and workflow automation capabilities that support legal and business functions across the firm.

Establishing evaluation, testing, monitoring, and quality standards for AI-enabled and non-deterministic systems.

Partnering with AI Platform Engineering to leverage shared model gateway, retrieval, evaluation, and orchestration services.

Full-Stack, Data & Integration Engineering

Developing modern web applications and services using contemporary front-end and back-end technologies.

Designing reusable application components, services, APIs, microservices, and integration patterns.

Integrating applications with internal platforms, document and knowledge management systems, search services, and other enterprise applications.

Building and maintaining data pipelines that transform structured and unstructured information for retrieval, evaluation, machine learning, and real-time inference.

Applying machine learning, natural language processing, and document-understanding techniques where appropriate.

Partnering with AI Platform Engineering on MLOps practices including model deployment, monitoring, drift detection, and retraining.

Software Engineering, Security & Operations

Establishing and championing engineering standards and best practices including automated testing, CI/CD, observability, release management, and secure development.

Leading technical design and architecture reviews and providing guidance on implementation approaches.

Building solutions in accordance with firm security standards, data governance policies, confidentiality requirements, and client obligations.

Implementing appropriate authentication, authorization, auditing, monitoring, and least-privilege access controls.

Designing appropriate human oversight and safety controls for AI-enabled applications, including protections against prompt injection, data exfiltration, and unintended actions.

Monitoring and optimizing application performance, scalability, reliability, and user experience.

Leading production incident investigations, root cause analyses, and long-term resiliency improvements.

Collaboration & Technical Leadership

Partnering with attorneys, business stakeholders, product owners, architects, and engineers to understand business needs and translate them into technical solutions.

Leading discovery and design discussions to identify high-value automation and AI opportunities.

Presenting technical concepts, solution approaches, business value, and associated risks to executive and non-technical stakeholders.

Mentoring engineers through code reviews, technical coaching, architecture discussions, and design guidance.

Influencing engineering standards, technology roadmaps, and software development best practices across teams.

Building consensus across engineering, infrastructure, information security, and business teams.

Qualifications:

Experience developing applications within Microsoft Azure environments.

Hands-on experience with agent frameworks, orchestration tooling, Model Context Protocol, and evaluation frameworks for non-deterministic systems.

Hands-on experience with a second major cloud platform — for example AWS (SageMaker, Glue, Athena, Lambda, ECS, S3)

Experience with data engineering, machine learning, MLOps, natural language processing, or document-understanding technologies.

Experience delivering technology in regulated or audited environments, including model validation or compliance-driven oversight requirements

Extensive experience designing and developing web applications, APIs, microservices, and distributed systems.

Demonstrated experience designing scalable enterprise architectures and leading technical delivery for complex, cross-functional initiatives.

Experience translating ambiguous business requirements into scalable technical solutions and leading initiatives from prototype through production.

Experience building production software using large language models, including retrieval, tool or function calling, and orchestration of multi-step workflows.

Strong understanding of software architecture, object-oriented design, distributed systems, application perform