• Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs. • Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference. • Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios. • Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs. • Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking. • Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains. • Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events. • Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks.

• Design, develop, and maintain end-to-end web applications using modern frontend and backend technologies. • Build responsive, high-performance user interfaces using React JS and related JavaScript or TypeScript frameworks. • Develop scalable backend services, RESTful APIs, and microservices using Node.js, Django, FastAPI, Flask, or similar frameworks. • Own full product development lifecycle activities including requirements analysis, architecture design, implementation, testing, deployment, monitoring, and continuous improvement. • Integrate AI capabilities into enterprise applications using LLMs, RAG pipelines, chatbot frameworks, and prompt engineering techniques. • Design and implement AI-enabled workflows including document ingestion, embeddings, vector search, retrieval optimization, and response generation. • Collaborate with product managers, UX designers, AI/ML engineers, DevOps teams, and business stakeholders to deliver reliable and user-focused solutions. • Ensure application security, scalability, performance, maintainability, and reliability across frontend, backend, database, and AI components. • Deploy, manage, and optimize applications and AI services on cloud platforms such as AWS, Google Cloud Platform (GCP), and Microsoft Azure. • Write clean, modular, well-tested, and maintainable code following software engineering best practices. • Mentor junior engineers, participate in code reviews, and contribute to technical design discussions and architecture decisions.

- **Prompt Engineering:** Design, test, and optimize complex prompts for accurate financial text and data extraction. - **Data Visualization:** Command generative AI tools and programmatic code to output rich analytics charts. - **Process Automation:** Build autonomous LLM workflows and agents to replace manual reporting processes. - **Model Customization:** Fine-tune or apply RAG (Retrieval-Augmented Generation) to models using financial documentation. - **Data Processing:** Clean, manipulate, and restructure raw financial files into optimized prompt payloads.

Role Description Ready to step into a legal career at the forefront of AI and innovation? Are you a lawyer or legal professional looking to move beyond traditional practice? Do you enjoy solving complex business challenges, advising senior stakeholders, and helping organisations embrace new technology? We are looking for a Legal Engineer to partner with corporate legal departments, helping them modernise legal operations through AI-powered solutions, workflow transformation, and strategic advisory. This is a highly consultative role that blends legal expertise, technology, and client engagement. You'll work closely with in-house legal teams to understand their operational priorities, identify opportunities for improvement, and demonstrate how our AI and legal technology solutions can transform the way they work. If you're passionate about legal innovation, enjoy building trusted relationships, and want to influence the future of corporate legal departments, this is an exciting opportunity to make a real impact. What You'll Be Doing - Partner with corporate legal departments to understand their workflows, strategic priorities, and operational challenges. - Advise clients on legal technology, AI adoption, legal operations, and workflow optimisation. - Deliver tailored product demonstrations, executive briefings, workshops, and training sessions. - Collaborate with Client Managers and Business Development teams to identify opportunities to expand existing customer relationships. - Gather customer feedback on product enhancements, emerging AI use cases, and market trends, sharing insights with Product and Engineering teams. - Become a trusted advisor to legal leaders navigating digital transformation. Qualifications - Juris Doctor (JD) and at least three years' experience in one or more of the following: - In-house legal experience within a Fortune 1000 or similarly complex organisation. - Legal operations, legal transformation, enterprise consulting, or legal technology implementation supporting corporate legal departments. - An Alternative Legal Services Provider (ALSP), advising large enterprise clients on legal strategy and operations. - A strong understanding of how corporate legal departments operate and the challenges they face. - Practical experience using generative AI tools and an appreciation of how AI can improve legal workflows. - Confidence discussing AI opportunities, governance, adoption, and risk with both legal and business stakeholders. - Experience engaging with General Counsel, Chief Legal Officers, Legal Operations leaders, and other senior decision-makers. - Excellent communication, presentation, facilitation, and consultative problem-solving skills. - The ability to travel approximately 50% to support customers and business needs. Preferred Experience - Legal operations or legal transformation initiatives. - AI implementation and technology adoption. - Contract Lifecycle Management (CLM), workflow automation, legal knowledge management, or enterprise legal technology platforms. - Enterprise-scale change management and digital transformation programmes.