Senior AI Software Engineer

Job Description

Join the Legal Tech Revolution at Litera

Are you ready to shape the future of how law is practiced? At Litera,we’reon a missionto Raise The Bar  for the legal profession by delivering transformational and globally-trusted solutions to law firms and corporate legal teams worldwide.

We’vebeen a leader inlegal techinnovation for 30 years and are leading the legal AI revolution to this day with mostof theworld’s largest law firms as our clients. Ifyou’repassionate about building AI-forward solutions that scale globally and want your work toimpactmillions of legal professionals worldwide, this is your opportunity to be part of an extraordinary teamthat’selevatingthe craftof law.

Hybrid Role: This positioninbased in Denver, CO and candidates should reside within reasonable commuting distance, as this role requires on-site presence at least three days per week
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The Generative AI Innovation Team is transforming how Litera—and its clients—leverage data for competitive advantage. As a Senior AI Engineer, you will play a critical role in shaping Litera’s GenAI strategy, architecture, and technical standards across both customer-facing products and internal platforms.

In this role, you will serve as a technical leader and subject-matter expert, partnering closely with engineering, product, security, and business teams. You will guide the design, development, and responsible adoption of Generative AI solutions, ensuring scalability, security, and long-term value. This is a high-impact opportunity to drive innovation atscalewithin a market-leading organization.

• Lead the design and development of enterprise-grade GenAI solutions, owning architecture decisions, technical patterns, and platform standards.

• Act as technical authority on LLMs, agentic systems, and emerging AI technologies, guiding adoption decisions and technical direction across engineering.

• Evaluate, prototype, and document emerging tools, platforms, and techniques — recommending strategic investments aligned with Litera’sroadmap.

• Own technical estimates, solution feasibility assessments, anddeliveryaccountability for complex, cross-functional initiatives.

• Establish and maintain GenAI governance standards, including safety, security, and responsibleuseguidelines applicable to production deployments.

• Define and own LLM observability and evaluation standards — including tracing, quality metrics, and monitoring forproductionAI systems.

• Champion software engineering best practices including secure coding, design patterns, and performance optimization.

• Contribute high-quality, scalable, and secure code with a strong focus on maintainability and reliability.

• 6+ years of professional software development experience , with at least 2 years focused on production
  
  GenAI systems and applications.

• Deep, hands-on experience with Large Language Models — including context engineering, prompt design, structured outputs, and LLM evaluation.

• Experience with LLM observability and evaluation tooling (e.g.,Lang Smith, RAGAS,Arize,Prompt Flow) and the ability to define and track GenAI quality metrics in production.

• Proficiency in Python , with working experience inLangGraphand/orLangChain.

• Familiarity with agent-based and multi-agent orchestration architectures.

• Experience with enterprise SaaS RESTful APIs and cloud-based backend development.

• Comfortable with relational data stores (PostgreSQL preferred; Azure SQL or SQL Server also acceptable).

• Solid background in testing practices — including unit, integration, and evaluation-layer testing for AI systems (e.g.,pytest).

• Hands-on experience building and shipping agentic workflows using
  
  LangGraph, Semantic Kernel, or comparable orchestration frameworks.

• Experience with LLM fine-tuning or working knowledge ofPyTorch, Tensor Flow, or scikit-learn at the application level.

• Strong foundation in RAG architectures, embeddings, vector databases, and semantic similarity.

• Experience evaluating or operationalizing AI-assisted development tooling (e.g., Git Hub Copilot, Cursor) within engineering teams.

• Strong familiarity with software architecture principles, security best…