AI Software Engineer

AI Software Engineer

What if your next role allowed you to shape AI-powered experiences that help professionals make better, faster decisions using trusted fiscal data?

Are you excited by building practical AI solutions, collaborating across disciplines, and turning emerging technology into valuable customer outcomes?

Lexis Nexis Risk Solutions provides customers with solutions and decision‑making tools that combine public and industry‑specific information with advanced technology and analytics to help them evaluate and predict risks and improve operational efficiency.

We use the power of data and advanced analytics to help our customers make better and faster decisions. By making information clearer and more actionable, we ultimately help make communities safer, insurance pricing more accurate, trade more transparent, business decisions simpler, and processes more efficient.

Taxes are complex. We make them manageable.

At Nextens, we build tax and compliance software that thousands of professionals rely on to stay compliant, work efficiently, and deliver accurate results. Our platform supports around 1 million filings every year, helping organizations navigate a constantly changing fiscal landscape with clarity and confidence.

We are looking for an AI Software Engineer to help expand AI capabilities across our tax-focused product ecosystem. The role supports our AI-powered tax assistant but is broader than RAG alone: it also includes generative AI features, workflow automation, and AI-powered insights from fiscal data. This is a medior role for someone who can contribute independently to well‑defined engineering tasks, work closely with senior engineers and domain experts, and grow their AI expertise while delivering practical product value.

• Build and improve AI‑powered product features, including assistants, RAG capabilities, workflow automations, and fiscal insight‑generation features.
• Develop AI application components such as data ingestion, retrieval, prompt orchestration, structured outputs, evaluation support, and monitoring hooks.
• Work with tax/domain experts to ensure AI outputs are accurate, explainable, grounded in fiscal data, and useful to users.
• Support evaluation and improvement of AI systems by reviewing model behaviour, feedback, test cases, and production signals.
• Collaborate with product, frontend, and engineering colleagues to turn AI capabilities into usable product experiences.
• Work effectively in AWS AI‑DLC workflows, using AI as an engineering collaborator while applying sound judgment, structured review, traceable decision‑making, and human approval at critical points.

• Experience as a software engineer, AI engineer, data engineer, machine learning engineer, or similar role.
• Good Python skills and experience building backend, data‑driven, automation, or AI/LLM‑powered application components.
• Familiarity with LLM application patterns such as RAG, embeddings, vector search, prompt engineering, structured outputs, and context management.
• Experience or strong interest in AI orchestration frameworks such as Pydantic AI, Lang Chain, Lang Graph, or similar tools.
• Ability to work with structured or semi‑structured data to generate insights, summaries, recommendations, or decision‑support features.
• Basic understanding of evaluation, monitoring, testing, secure development, data privacy, and responsible AI principles.
• Openness to an evolving, AI-native software delivery lifecycle, including rapid collaborative working sessions, experimentation, AI‑assisted execution, structured human review, and changing responsibilities as routine engineering tasks become increasingly automated.
• Familiarity with C#, .NET, Angular, or Type Script is a plus,…