Role Description This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). The AI Governance & Explainability Engineer is a hands-on technical role within the Data Governance team responsible for ensuring AI, GenAI, and Agentic AI solutions are explainable, governable, auditable, and production-ready. This role embeds governance directly into the AI technology stack, translating policies, regulatory expectations, and risk requirements into technical controls, automated checks, standardized artifacts, and release gates across the AI lifecycle. The role combines AI/ML engineering depth, GenAI & Agentic AI design knowledge, and governance discipline to ensure AI solutions deliver explainability, can be trusted, defended, and audited in production, particularly within the Microsoft Fabric and Purview ecosystem. Qualifications - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related field. - Minimum 7 years of experience in AI/ML engineering, data science, GenAI/LLMs, NLP, Agentic AI, data governance, or related roles. - Demonstrated experience operationalizing AI governance, explainability, and risk controls in production environments. - Deep understanding of Agentic AI architectures and lifecycle considerations. Requirements - Strong proficiency in Python with hands-on experience in AI/ML engineering workflows. - Working knowledge of Microsoft Fabric (Lakehouse, OneLake, notebooks, pipelines). - Experience with Microsoft Purview (catalog, lineage, classification, ownership). - Experience with AI/ML and GenAI tooling, including Azure AI Foundry / Azure ML, ML explainability libraries (e.g., SHAP), LLMs, RAG architecture, and prompt engineering. - Familiarity with Agentic AI frameworks and patterns (e.g., tool use, planning, reflection). - Experience integrating governance controls into CI/CD pipelines using GitHub or Azure DevOps. - Understanding of cloud platforms (Azure preferred; AWS/GCP a plus). - Experience producing audit-ready technical documentation and evidence artifacts. - Familiarity with reporting and visualization tools (e.g., Power BI) for governance and monitoring views. Benefits - Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model. - Acts as a role model within and outside AF. - Performs duties as workload necessitates. - Maintains a positive and respectful attitude. - Communicates regularly with the departmental leader about department issues. - Demonstrates flexible and efficient time management and ability to prioritize workload. - Consistently reports to work on time, prepared to perform duties of the position. - Meets Department productivity standards. Company Description This is a fully remote position requiring reliable high-speed internet access and a dedicated workspace. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Design and implement medallion architecture (bronze/silver/gold) using Delta Lake as the foundational layer across client environments. • Build and optimize scalable data pipelines using Apache Spark and Lakeflow (Declarative Pipelines, Jobs, and Connect for ingestion). • Architect and implement Unity Catalog as the backbone that governs data lineage, fine-grained access control (including row/column-level security), Lakehouse Federation, and Delta Sharing. • Drive best practices for performance tuning, cost governance, and compute optimization on Databricks. • Implement and optimize Databricks SQL for enterprise analytics, including AI/BI Dashboards and BI tool integration (Tableau, Power BI, Looker). • Design data models that serve both operational reporting and strategic analytics use cases. • Partner with business stakeholders to translate complex data requirements into reliable, performant solutions. • Build production AI solutions on the Databricks platform with tools including RAG pipelines using Mosaic Vector Search, agent development with the Mosaic AI Agent Framework, Model Serving endpoints, and external model APIs (OpenAI, Anthropic, Gemini, and others). • Leverage Mosaic AI, AI/BI Genie, and Databricks Apps to develop intelligent, data-driven applications that deliver real client value. • Stay current on Databricks AI capabilities and bring emerging patterns to the practice proactively. • Serve as a foundational technical resource for V2's Databricks practice, helping shape standards, methodologies, and delivery frameworks. • Operate across client engagements as a hands-on practitioner and technical advisor, translating business problems into platform solutions. • Support pre-sales and solutioning efforts: scoping engagements, contributing to proposals, and demonstrating credibility in client conversations. • Supercharge the broader technical team by leading code reviews, conducting formal and informal knowledge transfer, and elevating the people around you.

Role Description This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). The GenAI and Agentic AI Engineer is responsible for designing, developing, optimizing, and testing generative AI and agentic AI solutions to enable the production of accurate, relevant, and high-quality outputs across various business applications. The ideal candidate will have a strong background in AI, natural language processing, and RPA, and deep expertise in Large Language Models, RAG, prompt engineering, and Robotic Process Automation. The GenAI and Agentic AI Engineer will partner with stakeholders to drive business value to Arbitration Forums and our members through GenAI and Agentic AI solutions. This role excels at the implementation of the agentic AI development process, employing AI techniques to guide and enhance solutions, developing effective AI interactions and automations through proficient programming and testing. Qualifications - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Linguistics, or a related field. - Minimum of 7 years of experience in NLP, GenAI, LLMs, RAG, data governance, data science, or a related role. - Deep understanding of the components and development process of an Agentic AI solution. Requirements - Advanced programming knowledge, including mastery of programming languages such as Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. - Working knowledge of Azure AI Foundry and ML Studio. - Working knowledge of low code solutions, as well as tool integration and multi-agent collaboration. - Experience mapping and defining business processes and/or workflows for automation purposes. - Cloud computing knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure. - Deep understanding of containerization technologies like Docker and orchestration tools like Kubernetes for scaling AI solutions. - Experience combining design patterns like Tool Use, Reflection, and Planning for robust and solid automation. - Expertise in generative models such as generative adversarial networks (GANs) and variational autoencoders (VAEs). - Experience in Natural Language Processing (NLP) for text generation projects. - Working knowledge of techniques for text parsing, sentiment analysis, and the use of transformers like GPT models. - Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data. - Proficiency in prompt engineering for generative AI models (GPT-4, DALL-E, etc.) and experience creating and integrating RAG capabilities. - Strong understanding of natural language processing concepts and techniques. - Understanding of Agentic AI frameworks and tools, like CrewAI and Azure AI Foundry. - Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud). - Experience with AI tools, such as MS Azure ML, Databricks AI, Snowflake CortexAI, Dataiku. - Strong knowledge of data governance, data security, and compliance practices. - Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI). - Proficiency in programming languages such as Python, R, or SQL. Benefits - Support model and solution observability efforts to ensure adherence to company policies and enforce governance standards. - Other duties as assigned by manager or project needs. Company Description This is a fully remote position requiring reliable high-speed internet access and a dedicated workspace. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Lead a Forward Deployed AI engineering team and deliver AI-powered workflow transformation across various business functions. • Partner closely with the AI Platform team to ensure workflows transition cleanly to long-term ownership. • Drive deployments from discovery through production including workflow design, agent build, and human-in-the-loop checkpoints. • Serve as the primary contact for function heads throughout AI initiatives. • Maintain a prioritized pipeline of AI and automation opportunities.