• design, build, and operationalize scalable, secure, and responsible Generative AI solutions • drive the development and implementation of advanced machine learning models • collaborate with multiple departments to understand business requirements • interface with stakeholders to define performance metrics and evaluation methodologies • design and implement scalable machine learning systems • advise on optimization and improvement of data pipelines and model training processes • consult on and present technical findings to stakeholders • ensure compliance with data privacy regulations • manage team performance through feedback and performance reviews • stay up-to-date with the latest advancements in machine learning and technologies

Role Description As a LawVu Team Lead you will serve as an essential link between organisational vision and execution, requiring a unique blend of attributes to successfully ensure your team delivers on its goals (features, quality, timelines) while keeping the team healthy and effective. You are a bridge between engineers and stakeholders (product, design, management) so priorities, scope, and constraints need to be made clear and managed transparently for success. Reports to: This role reports to the Director of Engineering. Location: The preferred location is Tauranga or Wellington, but other New Zealand locations will be considered for the right person. What you’ll do - Collaborate: Work closely with product managers, designers, and engineers to drive innovation and development of product features. - Take Ownership: Own the full development lifecycle that includes AI-powered/platform features, from proof of concept to production and ongoing maintenance. - Ensure Sustainability: Contribute to the architecture design, balancing scalability with cost considerations. - Uplift: Mentor and guide junior engineers. - Personal Growth: Stay up to date with the latest developments in software engineering and AI. - Lead: Oversee the day-to-day activities of your engineering team, ensuring alignment with project goals and timely delivery of features. - Facilitate: Facilitate communication between cross-functional teams, resolving blockers and promoting a culture of knowledge sharing and continuous improvement. Qualifications - Product Engineering mindset. - Self-Starter: Take initiative and drive projects forward with minimal supervision. - Proactive: Anticipate challenges and address them before they become problems. - Problem Solver: Tackle complex issues with creativity and determination. - Resilient: Bounce back from setbacks and keep pushing forward. - Customer-Centric: Always keep the end-user in mind and strive to meet their needs. - Design-First: Prioritise design and usability in every feature you develop. - Value-Driven: Focus on delivering features that provide real value to our users. - Leadership Experience: Proven ability to lead technical teams, including setting priorities, managing workloads, and conducting performance reviews. - Strong Communication Skills: Ability to clearly articulate technical concepts to both technical and non-technical stakeholders and inspire team members toward shared objectives. Requirements - Full Stack Software Engineer with 8+ years of experience designing, building, and supporting large-scale systems. - Strong proficiency in C# .NET Framework / .NET Core, and REST API design and development. - Solid understanding of Azure PaaS and Azure Web App services. - Experience with GitHub. - AI Experience: Experience designing, conducting, and analysing experiments to validate hypotheses and optimize product features. - At least a good understanding of: - Retrieval-Augmented Generation - Evaluations - Azure Content Understanding - Semantic Kernel - MS Agent Framework - Integrating and deploying AI models and AI services in Cloud infrastructure - Comfortable working in an Agile development environment, with a strong focus on iterative development and continuous improvement. - Experience leading small-medium teams, having navigated complex problems both from a technical perspective, but product and people development as well. Benefits - Monthly wellness allowance for gym memberships, massages, childcare – you name it! - Health insurance cover. - Extended paid parental leave. - Extra paid day off on your birthday (cake not included but highly encouraged). - Share options – because you deserve a piece of the pie. - Home office allowance for remote employees. Company Description At LawVu, we believe in flexible working arrangements that let you balance work, life, and your passions. Join us early in our growth journey and participate in our success through our incentive scheme. Our collaborative and inclusive culture is something we’re immensely proud of. From day one, you’ll feel welcome and supported to do the best work of your life. - Inspire and Delight: We go the extra mile to create experiences that inspire and delight our customers. - Move Swiftly: We get things done quickly and efficiently. - Dig Deeper: No challenge is too big. We embrace challenges, learn from mistakes, and share knowledge. - Take Ownership: We take responsibility for our actions and their impact on the business. - Back Yourself. Back Others: We support and respect each other, building a high level of trust. - Bring Your Woo: We create a safe environment that fosters bringing your whole self to work. We’re committed to making LawVu one of the best places to work for everyone. We value diversity and promote a culture of inclusion. Ready to join the fun and make a real impact? Apply now and let’s transform the legal industry together!

• Explore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization. • Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans. • Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices. • Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency. • Ensure the security, scalability, and architectural integrity of feature designs through reviews across teams. • Mentor other data professionals (including MLEs) within the organization.

• Lead ML model creation, support foundational standardization • Create machine learning model architecture, parameters, and related technical specifications to accurately classify education finance data to a common reporting structure. • Guide staff in the sourcing, preparation of training data for machine learning models that map local accounting codes to standardized national categories. • Develop and implement model features derived from raw financial records, metadata, and related datasets. • Lead model iteration, evaluation, and improvement process with technical team members in support. • Provide analytical support in translation process. • Support processes and statistical rules for transforming current federal data into a nationally comparable, complete, and actionable dataset by identifying opportunities for efficiency and accuracy improvements. • Address reporting discrepancies—such as varying state treatments of teacher pensions and debt—to create a standardized foundational dataset.