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.

Role Description We are looking for a hands-on AI Engineer responsible for designing, developing, and operating AI-powered software systems that deliver immediate, real-world value. This role sits at the intersection of software engineering, product engineering, and applied artificial intelligence, with a strong focus on practical implementation rather than research or theoretical model development. As part of CodeNinja’s AI-first operating model, you will leverage LLMs, AI agents, and automation to fundamentally improve how software is built, deployed, and operated. Key Responsibilities - 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. Qualifications - 3+ years in AI, data science, and software engineering, with practical experience in banking projects. - Advanced Python (Pandas, NumPy, Matplotlib, Seaborn, LangChain, LlamaIndex). - Extensive hands-on experience with commercial LLMs, vector databases, and DataRobot, SAS EG. Benefits - Work at the forefront of AI-first software engineering, redefining how software is built today. - Build real, production-grade AI-enabled systems with measurable impact. - Operate with high ownership and autonomy, amplified by powerful AI tools. - Collaborate with talented engineers and product leaders in an innovation-driven environment. - Be part of a culture that values execution, learning, and engineering excellence. Disclaimer CodeNinja is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, and performance. Female and minorities are strongly encouraged and preferred to apply for the role.

• Work on meaningful, high-impact problems alongside experts in AI, data, and cybersecurity. • Shape systems that operate at real scale in a fast-moving threat landscape.

Role Description Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves: - Building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks. - Creating challenging tasks and evaluation criteria within realistic simulated environments: - Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history. - Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent. - Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient. - Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust. What this is NOT: - Not data labeling. - Not prompt engineering. - Not writing code from scratch - the agent writes most of the code; you guide and evaluate. Qualifications - 5+ years in software development. - Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis. - Experience writing tests (functional, integration). - English proficiency - B2+. Requirements Why this is hard: - Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. - You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. - Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds. Benefits - Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid. - Effort estimate: Tasks for this project are estimated to take 20 hours to complete, depending on complexity. - This is an estimate and not a schedule requirement; you choose when and how to work. - Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted. - Compensation: Up to $40/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.