Applied AI Engineer

## Applied AI Engineer Apply locations:
Raleigh, NCtime type:
Full time posted on:
Posted Yesterday job requisition :
R114310
** Applied AI Engineer*
* ** About the role
** Lexis Nexis Legal & Professional is hiring an Applied AI Engineer to help shape the next generation of AI-powered legal products and developer experiences. As an Applied AI Engineer at Lexis Nexis, you will partner with internal teams and enterprise stakeholders to help build AI-powered applications and workflows on top of Lexis Nexis AI platforms, legal content, and AI-powered workflows and agent-based capabilities.

You will work directly with engineering, AI engineering, and data science teams to design and implement production AI applications, agent workflows, and scalable LLM-powered experiences that support complex legal and professional workflows. This role sits at the intersection of AI engineering, data scientist, developer enablement, and customer engagement. You will partner with Product, Engineering, Applied Science, and AI Platform teams to support implementation decisions, accelerate AI adoption, and help teams adopt reusable AI engineering patterns and implementation best practices.

This is a deeply hands-on role focused on building, prototyping, and iterating on AI-powered experiences. The ideal candidate combines strong software engineering fundamentals with practical experience deploying LLM applications, agent systems, and AI-native workflows in production environments.  
** What you’ll do*
* ** Start with customers*
* * Spend real time with lawyers, legal operations teams, and our internal subject-matter experts — in their offices, on their calls, watching their workflows. Develop a strong understanding of customer workflows and operational challenges through direct engagement.
* Translate ambiguous, half-formed customer pain into crisp problem statements the team can build against.
* Collaborate closely with customers and internal stakeholders to prototype, validate, and refine AI-powered workflows and user experiences based on customer feedback and observed user needs.
* Bring the customer voice back into our roadmaps, our model choices, and our trade-offs.
* Occasional travel to customer sites may be required to better understand workflows and gather product feedback.
** Build AI-powered applications and workflows*
* * Contribute to AI-powered applications and workflows for legal and professional use cases, including leveraging existing RAG pipelines, research assistants, and related AI capabilities developed by ML engineering teams.
* Implement and iterate on LLM application capabilities such as prompt engineering, multi-step workflows, tool calling, and lightweight agent patterns in collaboration with machine learning engineering teams.
* Contribute to scalable orchestration layers for prompting, retrieval, and tool integration across AI services.
* Work with frameworks such as Lang Chain, Lang Graph, Llama Index, MCP/A2A, OpenAI SDKs, Google ADK, and/or Anthropic/Claude APIs to prototype and product ionize AI capabilities.
* Participate in experimentation, testing, and performance optimization activities for LLM-based applications in production environments.
** Contribute to AI Engineering Enablement*
* * Support adoption of AI engineering practices by helping software engineering teams incrementally integrate machine learning and generative AI capabilities into existing products and workflows, in collaboration with AI/ML engineering teams.
* Promote reusable AI/ML engineering standards, tooling, and best practices that reduce friction for teams adopting AI and machine learning technologies, while aligning with recommendations from data science and AI platform teams.
* Help software engineers expand their capabilities in ML-oriented development for applicable use cases without requiring deep data science specialization.
* Support teams in adopting AI-assisted development workflows through prototyping, architecture collaboration, and hands-on engineering support.
* Contribute to engineering for LLM applications, AI workflows, and AI-enabled product development.
* Assist in building evaluation, monitoring, and observability…