Director Software Engineering - Customer Innovation Lab (New York, NY)

This job is with LexisNexis Legal & Professional®, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

** Please note that this position will be located in New York City and will require full-time, on-site presence. If you are unable to align with this requirement, please consider other roles across LexisNexis that might allow for hybrid and/or remote work. **

About our Team :

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX , a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case.

About the Role :

The Director Software Engineering position is responsible for all aspects of technology and development leadership for a major software product or system(s). This position sets the architectural standard for the workgroup as well as providing the team with day-to-day management and direction to accomplish on-time, efficient delivery of product development goals. Additionally, the position will also lead a development team to perform research, design, and software development assignments within a software functional area and provide direct input to project plans, schedules, and methodology in the development of cross-functional software products. The Director is expected to maintain direct engagement with customers, end users, and internal subject-matter experts so that technical strategy, roadmaps, and architectural trade-offs are grounded in observed customer workflows rather than secondhand reports. Above all, the Director is expected to be deeply AI-fluent - conversant in modern generative AI, large language model (LLM), and agentic approaches - and to set the standard for how the team applies AI across the software development lifecycle, from prototyping to production. As a recognized technical thought leader, the Director champions AI-native engineering practices both internally and externally, mentors engineers in raising their own AI fluency, and helps shape the organization's point of view on building trustworthy, enterprise-grade AI systems for the legal market.

Requirements :

• 12+ years of Software Development experience

• 5+ years of Software Development management experience

• BS Engineering/Computer Science or equivalent experience required; advanced degree preferred

• Demonstrated AI fluency: hands-on experience building, shipping, and operating generative AI and LLM-powered applications in production, including retrieval-augmented generation (RAG), prompt engineering, tool calling, orchestration, and agent-based workflows.

• Working familiarity with modern AI engineering frameworks and tooling (e.g., LangChain, LangGraph, LlamaIndex, MCP/A2A, OpenAI, Google, and/or Anthropic/Claude APIs) and with AI evaluation, observability, guardrails, and responsible-AI deployment practices.

• Demonstrated technical thought leadership - such as open-source contributions, technical writing or blogging, conference speaking, internal evangelism, or leading developer-enablement initiatives that advanced AI adoption across teams.

Responsibilities :

• Lead internal and external technology resources.

• Successfully partner and lead large offshore resources in solving complex business needs.

• Perform reviews to ensure enterprise and architectural standards and processes are followed.

• Complete management responsibilities to include performance management, hiring, and coaching of staff.

• Utilize best practices and understand emerging trends.

• Write advanced complex code for computer systems and serve as a senior source of expertise.

• Manage system and user acceptance testing cycles to ensure accurate and quality business solutions.

• Lead the development of technical standards and perform reviews to ensure enterprise and architectural standards and processes are followed.

• Recommend technical strategy and direction across functional area.

• Participate in development and evolution of architecture.

• Set the AI fluency bar for the team: define and champion how generative AI, LLMs, and agentic patterns are applied across the software development lifecycle, and ensure the group adopts a flexible, multi-model approach that selects the best model for each legal use case.

• Drive the design and delivery of AI-powered applications and workflows - including RAG pipelines, research assistants, prompt and orchestration layers, tool calling, and lightweight agent patterns - in partnership with AI/ML engineering, data science, and AI platform teams.

• Raise the AI fluency of the broader engineering organization: coach and upskill software engineers in AI-assisted development and ML-oriented practices, and establish reusable AI engineering standards, tooling, evaluation, and observability that reduce friction for teams adopting AI.

• Act as a technical thought leader on AI - representing the team through technical writing, talks, workshops, hackathons, and developer-enablement initiatives, and contributing learnings back to shared AI platform capabilities and the wider engineering community.

• Stay current with the rapidly evolving AI landscape and translate emerging research, models, and tooling into pragmatic, responsible engineering decisions that uphold the accuracy, transparency, and reliability required in the legal industry.

• Provide design input across a product.

• Spend time directly with customers, end users, and internal subject-matter experts - in their offices, on their calls, and observing their workflows - to develop firsthand understanding of operational challenges.

• Translate ambiguous, half-formed customer pain into crisp problem statements the team can build against.

• Partner with customers and internal stakeholders to prototype, validate, and refine workflows and user experiences based on direct feedback and observed user needs.

• Bring the customer voice back into roadmaps, technical strategy, and architectural trade-offs.

• Serve as a primary technical point of contact for customers and external technology resources, including communicating clearly with non-engineering audiences (e.g., lawyers, legal operations) and adapting language to the audience without dumbing it down.

• Consult with stakeholders to find alternative work-arounds during system outages.

• Travel to customer sites as needed to observe workflows and gather product feedback.

• Serve as acknowledged go to person on coding and technical issues.

• Interface with other technical personnel or team members to finalize requirements.

• Write and review portions of detailed specifications for the development of system components of moderate complexity.

• Complete bug fixes.

• Design and work with complex data models.

• Carry out management responsibilities in accordance with the organization's policies, procedures, and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; and addressing complaints and resolving problems.

• Ensure all staff is provided with training and resources needed to perform their jobs to the most outstanding degree possible. Ensure all staff is provided with frequent feedback and coaching in order to meet and exceed individual and team performance goals consistently.

• Manage and encourage new ideas from staff to foster improvements through innovations.

• Empower the staff to be accountable and responsible for their own actions and decisions.

• Seek diverse ideas and perspectives from a variety of sources to create better solutions, products, and services.

• All other duties assigned.

Technical Skills :

• Key experience and proven competencies in technologies associated with responsibilities.

• Strong AI fluency: proven, hands-on command of generative AI and LLM application development - prompt engineering, retrieval-augmented generation (RAG), tool calling, orchestration, context management, structured generation, and agent-based workflows.

• Practical knowledge of modern AI engineering frameworks and tooling (e.g., LangChain, LangGraph, LlamaIndex, MCP/A2A, OpenAI, Google, and/or Anthropic/Claude APIs) and of deploying and operating AI systems in cloud-native environments (AWS, Azure, or GCP).

• Familiarity with AI evaluation frameworks, observability and production monitoring, guardrails, policy enforcement, and responsible-AI deployment for trustworthy, enterprise-grade systems.

• Proven ability to provide technical thought leadership - communicating AI concepts clearly to engineering and non-engineerin]]>