AI Application Developer

Eversheds Sutherland (US) LLP•,

43d•$150,000 - $205,000•Remote

About The Position

Eversheds Sutherland's US Innovation Team is seeking an experienced AI Application Developer to drive the design, development, and deployment of artificial intelligence solutions across the firm. In this role, you will be the technical authority on all things AI — from architecting enterprise-grade machine learning systems to building intelligent agents that transform how our lawyers and business professionals work. You will collaborate closely with attorneys, business stakeholders, and IT to translate complex legal and operational needs into scalable, secure, and elegant technology solutions.

Requirements

5+ years of software or AI development experience, with at least 2 years in a technical lead or architect role.
Hands-on expertise with large language models (LLMs), prompt engineering, fine-tuning, and orchestration frameworks (e.g., LangChain, Semantic Kernel, or equivalent).
Demonstrated experience building RAG applications, including vector database integration (e.g., Azure AI Search, Pinecone, Weaviate) and document chunking strategies.
Proficiency with Azure AI Foundry (Azure OpenAI Service, AI Studio, Azure Machine Learning) and related Azure services.
Experience with Microsoft Power Platform — including Power Automate, Power Apps, and AI Builder.
Strong SQL skills, including data modeling, query optimization, and integration with AI/ML pipelines.
Experience implementing MCP or similar agent communication protocols to connect AI models with enterprise tools and APIs.
Proficiency in Python and/or JavaScript/TypeScript for AI and application development.
Solid understanding of DevOps practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), infrastructure as code, and environment management.
Experience with Git-based version control, branching strategies, and collaborative code management.
Demonstrated ability to manage competing priorities in a fast-paced environment, including collaborating with stakeholders across practice groups and business services to maintain ruthless prioritization of the most impactful work.
Familiarity with multi-agent orchestration patterns and agentic workflow design.
Knowledge of responsible AI principles, including bias mitigation, model explainability, and privacy-preserving techniques.

Nice To Haves

Prior experience working in a law firm, legal department, or professional services environment.
Microsoft certifications in AI, Azure, or Power Platform.
Experience with enterprise knowledge management platforms or legal document management systems (e.g., iManage, NetDocuments).
Familiarity with SharePoint, Microsoft 365, and Teams integration for AI application delivery.

Responsibilities

Lead end-to-end development of AI-powered applications, including large language model (LLM) integrations, retrieval-augmented generation (RAG) pipelines, and autonomous agent frameworks.
Design and implement Model Context Protocol (MCP) integrations to enable interoperability between AI agents and firm systems.
Architect solutions on Azure AI Foundry, ensuring alignment with enterprise security, compliance, and scalability requirements.
Develop and maintain AI workflows using Microsoft Power Platform, including Power Automate, Power Apps, and AI Builder, to extend AI capabilities to non-technical users across the firm.
Build and optimize SQL-based data layers to support AI applications, reporting, and analytics pipelines.
Establish and champion coding standards, code review processes, and documentation practices for the innovation team.
Define and implement DevOps pipelines (CI/CD) for AI and software projects, ensuring reliable deployment, monitoring, and rollback capabilities.
Recommend and maintain version control strategies using Git, with branching models appropriate for collaborative legal technology development.
Evaluate emerging AI frameworks, tools, and methodologies and provide recommendations for adoption where appropriate.
Design AI systems with firm-wide deployment in mind, accounting for multi-office use, role-based access control, data privacy, and performance at scale.
Partner with IT, Risk, and Compliance teams to ensure all AI solutions meet regulatory obligations and internal governance standards.
Create architecture decision records (ADRs) and technical roadmaps to guide long-term platform development.
Lead technical onboarding and knowledge transfer for new team members and firm stakeholders.
Act as a trusted technical advisor to firm leadership, practice groups, and business services teams on AI feasibility, risks, and opportunities.
Translate business requirements into technical specifications and lead solution design sessions with cross-functional teams.
Present technical concepts clearly to both technical and non-technical audiences.