Innovations and AI Solutions Engineer

Job description

Wilson Sonsini is the premier legal advisor to technology, life sciences, and other growth enterprises worldwide. We represent companies at every stage of development, from entrepreneurial start-ups to multibillion-dollar global corporations, as well as the venture firms, private equity firms, and investment banks that finance and advise them. The firm has approximately 1,100 attorneys in 17 offices: 13 in the U.S., two in China, and two in Europe. Our broad spectrum of practices and entrepreneurial spirit allow exceptional opportunities for professional achievement and career growth. The Innovation and AI Solutions Engineer position is part of the firm’s Innovation Department. This position will be responsible for developing, optimizing and growing the firm’s corpus of innovation and AI solutions for both practice and enterprise side use cases, as well as optimizing data collection and flows across these solutions. The role will support our attorneys and staff with software development, low/no-code solutions, and data initiatives. The Innovation and AI Solutions Engineer is a self-directed, people-oriented employee who is comfortable supporting the development and data needs of the organization, including clients, attorneys, practice groups and administrative teams. This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities Build and maintain innovation and AI solutions, assembling and working with large, complex data sets that meet business and technical requirements. Support innovation projects by facilitating discussions with management and other departments, developing business processes, implementing data integrations and recommending best practices for the effective use of data and analytics tools. Identify, design, and implement process improvements by automating manual work, optimizing data delivery, and building efficient integration infrastructure across a wide variety of data sources and solutions. Apply analytics, statistics, and computational techniques - including common NLP and machine learning methods - to surface actionable insights on customer acquisition, operational efficiency, billing, case outcomes, and other key business and legal practice metrics, researching and applying new models as needed for creative problem solving. Ensure firm and client data security across multiple office locations, data centers, vendors, and applications. Use version control systems such as GitHub and maintain clear, efficient documentation of code and end-to-end processes. Experience, Knowledge and Abilities Development, Data, and AI Solutions Strong software development skills with the ability to quickly prototype, build, and iterate on code-based solutions to solve business problems, moving efficiently from concept to implementation. Experience designing and developing full solutions from data ingestion and transformation through to deployed, working applications. Familiarity with CI/CD practices, build agents, environment promotion, and release safety to support reliable, efficient delivery of code-based solutions. Knowledge of SQL and relational databases, including advanced query authoring, procedure creation and basic database management. Strong analytical skills working with structured and unstructured datasets. Experience analyzing business problems, data integrations, and processes to identify and resolve issues. Experience developing processes and infrastructure that support data transformation, integrations, data structures, metadata, dependency, and workflow management. Experience utilizing & deploying Azure cloud resources, such as AI Search, Logic Apps, Containers & Azure Functions. Ability to troubleshoot infrastructure issues across applications, platforms, and cloud layers. Understanding of secure cloud operations, including RBAC, secrets management and familiarity with network roles. Experience with AI/ML data preparation, including feature engineering, data preprocessing, and dataset versioning for machine learning and AI workflows. Knowledge of data bias detection and mitigation techniques to help ensure AI models are fair and representative across different legal contexts. Experience with vector databases and embeddings for semantic search and retrieval-augmented generation (RAG) applications. Familiarity with CI/CD pipelines, build agents, environment promotion, and release safety Collaboration and Professional Skills Ability to collaborate with cross-functional teams, stakeholders, and application engineers, translating operational needs into practical improvements in a dynamic environment. Ability to handle sensitive and confidential information responsibly. Ability to learn new tools and coding languages as required. Ability to organize tasks and priorities under minimal supervision. Technological Proficiency Experience in applying the following technologies: Programming and scripting languages: Python, R, JavaScript, SQL Version control using Git SQL Server, T-SQL, Stored Procedures Data warehousing experience focused on ETL processes API integration and development Integrating existing large language models (LLMs) into applications via API Developing and applying machine learning models and integrating AI models using Python, R, SQL, and Azure Embedding models: familiarity with sentence transformers, OpenAI embeddings, or domain-specific legal embeddings Model Context Protocol (MCP) integrations, including writing simple MCP servers on top of existing applications to expose their functionality to AI models CI/CD pipeline building and maintenance using Azure DevOps Technical documentation using Markdown Cloud and infrastructure experience with: Azure, including AKS, ACR, Key Vault, Blob Storage Terraform Azure Pipelines Law firm experience a plus Requirements 5+ years of experience in a Data Engineer/DataOps-DevOps role. BS and/or graduate degree in Computer Science, Data Science, Data Analytics, Information Systems or e