AI Engineer

ESSENTIAL JOB FUNCTIONS

• Partner with attorneys, practice groups, legal project management, knowledge management, finance, risk, client development, and business-services teams to understand workflows, pain points, and desired outcomes.
• Facilitate technical discovery sessions; assess business problems for AI, automation, workflow, integration, and custom application opportunities.
• Rapidly design and develop proof-of-concept and pilot solutions using approved AI platforms, APIs, low-code tools, workflow automation platforms, and custom development technologies.
• Build secure AI-enabled applications, including generative AI assistants, document and knowledge-search solutions, RAG applications, workflow copilots, intelligent agents, and decision-support tools.
• Develop and maintain integrations among firm applications, document repositories, knowledge systems, data platforms, collaboration tools, and approved third-party services.
• Design AI solutions that appropriately address data classification, confidentiality, ethical use, model limitations, human review, auditability, access controls, retention, and regulatory obligations.
• Work with enterprise solutions architecture, information security, privacy, records management, risk management, and legal teams to ensure solutions meet global firm standards before production deployment.
• Evaluate and select appropriate technical approaches based on business value, solution complexity, data sensitivity, scalability, supportability, and time-to-value.
• Develop reusable components, integration patterns, prompt libraries, evaluation methods, documentation, and technical standards that accelerate future AI and automation delivery.
• Conduct testing, quality assurance, user acceptance testing, model evaluation, and performance monitoring for AI-enabled solutions.
• Create technical documentation, architecture diagrams, support materials, operating procedures, and knowledge-transfer artifacts.
• Transition mature solutions to the appropriate applications support and operations or enterprise application development, ensuring clear ownership, support readiness, and lifecycle plans.
• Monitor deployed solutions for performance, reliability, adoption, model behavior, security concerns, and opportunities for iterative improvement.
• Stay current on AI engineering practices, legal-industry AI use cases, emerging tools, AI governance requirements, and applicable technology trends.
• Participate in intake prioritization, solution estimation, roadmap planning, vendor evaluations, and innovation portfolio reporting.
• Partner with Legal, Risk, Security, and Compliance Teams to ensure AI initiatives meet applicable legal and regulatory obligations.
• Ensure AI systems handling client or confidential information meet applicable privacy, security, and data handling requirements across all operating jurisdictions.

Knowledge & Experience

• With Generative AI, Model Context Protocol (MCP), Azure/OpenAI, Large Language Model (LLM), Microsoft CoPilot, prompt engineering, retrieval-augmented generation, embeddings, vector databases, AI agents, model evaluation, and responsible AI practices.
• Application development concepts, including APIs, microservices, web applications, databases, authentication, authorization, logging, monitoring, testing, and CI/CD practices.
• Cloud and enterprise technology environments, including secure API integration, DevOps, identity and access management, data governance, and application lifecycle management.
• Automation and orchestration technologies, such as workflow platforms, robotic process automation, low-code/no-code development tools, and integration platforms.
• Data privacy, confidentiality, information security, records retention, and risk considerations applicable to professional-services or legal environments.
• Software development methodologies, including Agile, Kanban, rapid prototyping, product discovery, and iterative delivery.
• Legal-industry workflows and systems is preferred, including document management, knowledge management, time and billing, matter management, legal research, e-discovery, client intake, and financial systems.

Skills

• Strong software engineering skills in one or more modern programming languages, such as Python, JavaScript/TypeScript, C#, ASP.NET Core, SQL, or similar technologies.
• Ability to build and deploy AI-enabled applications using APIs, SDKs, orchestration frameworks, cloud services, and enterprise platforms.
• Ability to translate ambiguous business needs into clearly defined user stories, technical requirements, solution designs, and delivery plans.
• Strong consultative and communication skills, with the ability to work effectively with attorneys, senior business leaders, technical teams, vendors, and nontechnical users.
• Ability to explain AI capabilities, limitations, risks, and recommended controls in clear, practical language.
• Strong analytical, problem-solving, and systems-thinking abilities.
• Ability to balance speed and experimentation with security, quality, governance, maintainability, and long-term supportability.
• Experience designing user-centered solutions and incorporating feedback into rapid iterations.
• Strong organization and prioritization skills in a fast-moving environment with multiple concurrent initiatives.
• Knowledge of responsible AI frameworks such as React and emerging international AI regulations.

Interests

• Genuine curiosity about applying AI to meaningful legal, client-service, and business-operations challenges.
• Interest in working directly with end users and seeing solutions through from discovery to measurable adoption.
• Interest in responsible AI, data protection, human-centered design, and practical technology governance.
• Enthusiasm for experimentation, continuous learning, emerging technologies, and building reusable enterprise capabilities.
• Interest in improving how attorneys and professional-services teams access knowledge, complete work, collaborate, and serve clients.

Education & Experience

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or a related technical discipline required; equivalent combination of education, training, and relevant experience may be considered.
• Minimum of 5 years of experience in software engineering, application development, automation, systems integration, data engineering, or related technical roles.
• Minimum of 2 years of experience designing, developing, or deploying AI-enabled, machine-learning, generative AI, automation, or intelligent workflow solutions preferred.
• Experience building applications using large language model APIs, RAG architectures, AI orchestration frameworks, Model Context Protocol (MCP), Azure/OpenAI, vector search technologies, or agentic workflow patterns strongly preferred.
• Experience with cloud platforms such as Microsoft Azure or Amazon Web Services.
• Experience with enterprise integrations, APIs, identity and access management, secure development practices, and application lifecycle management required.
• Experience in a law firm, legal technology provider, consulting firm, financial-services organization, or other regulated professional-services environment strongly preferred.
• Experience working with cross-functional stakeholders and delivering technology solutions from discovery through production deployment required.
• Relevant certifications in cloud engineering, AI, software development, security, automation, Agile delivery, or legal technology are preferred but not required.