AI Application Developer

Role overview

The AI Application Developer on Eversheds Sutherland’s US Innovation Team will serve as the technical authority for AI solutions across the firm—designing, building, and deploying applications that integrate LLMs, RAG pipelines, and intelligent agents. You’ll partner with attorneys, business stakeholders, and IT to translate complex legal and operational needs into secure, scalable technology.

Responsibilities

• AI solution architecture & development
  • Lead end-to-end development of AI-powered applications, including LLM integrations, RAG pipelines, and autonomous agent frameworks.
  • Design and implement Model Context Protocol (MCP) integrations for interoperability between AI agents and firm systems.
  • Architect solutions on Azure AI Foundry while meeting enterprise security, compliance, and scalability requirements.
  • Develop and maintain AI workflows using Microsoft Power Platform (Power Automate, Power Apps, AI Builder) for non-technical users.
  • Build and optimize SQL-based data layers to support AI applications, reporting, and analytics.
• Technical leadership & best practices
  • Establish coding standards, code review processes, and documentation practices.
  • Define DevOps pipelines (CI/CD) for AI and software projects, including monitoring and rollback.
  • Recommend and maintain Git version control strategies suitable for collaborative development.
  • Evaluate emerging AI frameworks/tools/methodologies and recommend adoption.
• Firm-wide scalability & governance
  • Design AI for firm-wide deployment (multi-office, role-based access control, data privacy, performance at scale).
  • Partner with IT, Risk, and Compliance to meet regulatory and governance requirements.
  • Produce ADRs and technical roadmaps.
  • Lead onboarding and knowledge transfer for new team members and stakeholders.
• Stakeholder collaboration
  • Advise leadership and practice/business groups on AI feasibility, risks, and opportunities.
  • Translate business requirements into technical specifications and lead solution design sessions.
  • Present technical concepts to both technical and non-technical audiences.

Requirements

• 5+ years of software or AI development; 2+ years in a technical lead or architect role.
• Hands-on experience with LLMs, prompt engineering, fine-tuning, and orchestration frameworks (e.g., LangChain or Semantic Kernel).
• Experience building RAG applications with vector database integration (e.g., Azure AI Search, Pinecone, Weaviate) and document chunking strategies.
• Proficiency with Azure AI Foundry (including Azure OpenAI Service, AI Studio, Azure Machine Learning).
• Experience with Microsoft Power Platform (Power Automate, Power Apps, AI Builder).
• Strong SQL skills (data modeling, query optimization, AI/ML pipeline integration).
• Experience with MCP (or similar agent communication protocols).
• Proficiency in Python and/or JavaScript/TypeScript.
• Solid understanding of DevOps practices, including CI/CD (Azure DevOps or GitHub Actions), and infrastructure as code.

Nice-to-haves

• Experience and comfort with agent communication protocols and enterprise AI governance processes across multiple stakeholders and offices.