Senior AI Software Engineer | Python | Azure | Legal Tech

Senior AI Software Engineer is required to design and build secure, production-ready AI solutions for one of the top five law firms in the US and most prestigious legal organisations globally . With a market leading budget invested in AI, technology and innovation , the firm is building serious engineering capability around Generative AI and creating innovative AI solutions that will fundamentally change how its attorneys serve clients and operate at scale.

Location: New York or Chicago - Hybrid 3 days per week. (can’t sponsor H1B, muts be eligable to work)

This is an opportunity to work at the forefront of Generative AI, LLMs, RAG, AI agents and cloud engineering , taking sophisticated AI solutions from experimentation and evaluation through to production deployment and monitoring.

You’ll join a growing Innovation Engineering function and work alongside engineers, data scientists, innovation leaders and attorneys to solve complex, high-value problems. You’ll develop AI-powered products supporting areas such as document analysis, summarisation, legal research and diligence, while helping establish reusable AI engineering standards and architecture across a global organisation.

The position offers a base salary of $176,000–$264,000 , alongside comprehensive benefits, paid time off, retirement benefits and ongoing learning and development opportunities.

Key skills required for the Innovation AI Developer

• 4+ years of relevant experience across technical, professional services or legal environments, ideally within a law firm or similarly complex or regulated organisation.
• Strong Python development skills together with proficiency in SQL, APIs, databases and structured and unstructured data .
• Hands-on experience building applications using LLMs and Generative AI , with technologies such as OpenAI, Azure OpenAI, Hugging Face, LangChain, LangFlow or comparable frameworks.
• Strong experience designing and implementing RAG pipelines and AI agents , including vector databases such as Pinecone and/or knowledge graph-backed architectures.
• Experience designing secure, scalable AI solutions within Microsoft Azure .
• Familiarity with Docker, Kubernetes and CI/CD ; experience with Azure AI Studio, Azure Cognitive Search and Azure Cosmos DB would be advantageous.
• Experience developing LLM evaluation frameworks using Promptfoo, OpenAI Evals, LangSmith or similar tooling.
• Experience building accessible internal AI applications using Retool, Streamlit or Gradio .
• Understanding of AI security, privacy and governance requirements when working with highly sensitive information.
• Ability to lead technical discovery, quantify ROI, establish acceptance criteria and communicate complex technical concepts to non-technical stakeholders.
• Bachelor’s degree required, preferably in Computer Science or a related discipline.
• Strong communication and stakeholder management skills, with the ability to influence technical decisions and support the development of other engineers.

What you’ll do as an Innovation AI Developer

• Design and build secure internal AI products and workflows using LLMs, vector databases, orchestration frameworks and modern UI technologies .
• Develop RAG pipelines, AI agents and intelligent applications supporting document analysis, diligence, summarisation and legal research.
• Architect resilient AI solutions on Microsoft Azure , collaborating with infrastructure and security teams across cloud, on-premise and hybrid environments.
• Take AI products through the complete engineering lifecycle, from experimentation and prototyping through evaluation, production deployment and monitoring.
• Build sophisticated evaluation frameworks measuring accuracy, robustness, safety, business value and use-case alignment .
• Partner with attorneys, business leaders and technical stakeholders to identify high-value AI opportunities and turn complex requirements into practical products.
• Advise on prompt engineering, model selection, architecture and evaluation methodologies .
• Build reusable libraries, technical documentation and solution patterns to accelerate AI development across the firm.
• Evaluate emerging AI technologies, open-source frameworks, vendor platforms and third-party applications.
• Support AI pilots, demonstrations, user training and feedback programs while contributing to i…