Role Description The Sr. Staff AI Engineer is a senior leader within Blue Yonder’s Supply Chain Advisory AI team, responsible for designing, building, and operationalizing advanced AI and machine learning driven solutions that address complex, real world supply chain challenges. This role blends supply chain domain expertise with hands-on ML and GenAI agent development, to accelerate AI adoption and deliver measurable operational and financial outcomes. The role partners closely with customers, product, engineering, and advisory teams to translate business problems into scalable AI solutions. This role serves as a trusted expert who can clearly articulate value, guide implementation, and drive sustained adoption across customer environments. We are looking for strong candidates with hands-on architecture and engineering experience, building and deploying AI agents for enterprise customers within a professional services team. What You’ll Be Doing - AI Solution Design, Architecture & Delivery: - Design, build, and deploy machine learning models across the full solution lifecycle, including data preparation, validation, deployment, and monitoring. - Architect and develop GenAI‑powered agents, including prompt and context engineering, retrieval‑augmented generation (RAG), multi‑agent orchestration, and integration with ML models and optimization solvers. - Translate complex customer business problems into AI‑driven predictions and recommendations that deliver measurable outcomes such as cost reduction, service improvement, and revenue uplift. - Lead and contribute to rapid customer POCs, experiments, and pilots, iterating solutions toward scalable, production‑ready implementations. - Customer Advisory & Adoption: - Work directly with customers to build trust, demonstrate explainability, and operationalize AI by embedding agents and models into daily workflows. - Guide customers through adoption and change management, supporting the transition from experimentation to sustained AI‑driven transformation. - Confidently communicate AI strategy, risks, and value to technical, business, and executive stakeholders. - Engineering & Platform Integration: - Partner with engineering teams on full‑stack development, including front‑end and back‑end integration, microservices extensions, and CI/CD enablement. - Ensure AI solutions integrate effectively within enterprise platforms and the Blue Yonder ecosystem, balancing scalability, performance, and cost. - Thought Leadership & Practice Contribution: - Act as a thought leader within the AI Advisory community, mentoring peers and contributing to best practices and delivery standards. - Stay current on advancements in ML, GenAI frameworks, and supply chain AI applications, applying new techniques where they provide tangible customer value. Qualifications - 8 years of hands-on professional experience in data science, machine learning, advanced analytics, AI engineering, data engineering or software engineering within enterprise-scale environments. - Strong hands-on experience with Python, SQL, and modern data engineering practices, including buildable scalable data pipelines, ETL/ELT workflows, data integration processes, and production-grade analytics or AI/ML solutions. - Must have demonstrated experience with modern AI/GenAI capabilities, including agent-based systems, RAG architecture, prompt and context engineering, multi-agent orchestration, model fine-tuning, and LLM-based solution design. - Strong collaboration skills and ability to operate effectively in ambiguous, complex problem spaces. Preferred Qualifications - Bachelor’s or Advanced Degree (Masters, PHD, etc.) in Data Science, Computer Science, Engineering, or a related field, or equivalent practical experience. - Familiarity with Snowflake Cortex, semantic layers, Cortex Analyst/Agents, or similar AI-enabled data platform capabilities is preferred. - Experience with knowledge graphs, ontology-driven modeling, graph-based reasoning, and platforms such as Relational AI, Neo4j, or similar technologies to enhance AI agents, RAG workflows, contextual reasoning, explainability, and enterprise decision intelligence. - Deep supply chain domain expertise across one or more functional areas, including; planning, merchandising, allocation, replenishment, fulfillment, procurement, or returns. - Experience across at least one industry vertical; Manufacturing, Retail, or Logistics Service Providers (e.g., Automotive, High Tech, Hardlines, Softlines, Grocery). - Experience acting as a mentor or technical leader within AI or advanced analytics teams. Benefits - Comprehensive Medical, Dental and Vision - 401K with Matching - Flexible Time Off - Corporate Fitness Program - A variety of voluntary benefits such as; Legal Plans, Accident and Hospital Indemnity, Pet Insurance and much more

Role Description King’s InterHigh is a flexible and inclusive online school that empowers students to succeed both academically and personally. Combining nearly two decades of online education expertise with over 50 years of academic excellence from the King’s College schools, King’s InterHigh delivers a personalised education within a supportive and welcoming community. Students attend live, teacher-led virtual lessons each school day, where highly trained online educators create engaging and interactive learning experiences that encourage collaboration, participation and a genuine love of learning, enabling every student to reach their full potential. As part of our continued growth and commitment to delivering outstanding online education, King's InterHigh is introducing the Mentored Pathway - a new premium programme that pairs students with a named, qualified Teacher Mentor. As a Teacher Mentor, you will support students’ academic progress through regular guidance, oversight and family communication. Qualifications - Be an experienced, qualified teacher (this post is not suitable for ECTs) - Excellent written and verbal communication skills - Experience in communicating proactively with parents and carers in a professional setting - Hold relevant and up-to-date safeguarding training Requirements - Provide tailored individual support to students - Maintain continuous oversight of each student's progress across all subjects, proactively identifying concerns early - Support students with academic planning, organisation, and independent study habits - Act as the primary academic point of contact for families, communicating proactively throughout the year - Help students engage with the wider KIH offer, including clubs, enrichment, and academic support - Collaborate with subject teachers and pastoral colleagues, escalating concerns to the appropriate team when needed Benefits - Work in state-of-the-art facilities alongside industry-renowned educators - Enjoy industry-leading professional development - Exceptional career opportunities and mobility across our group Company Description Inspired Education is the leading global group of premium schools, with a portfolio of 125 premium private schools spanning 6 continents which utilise proven educational practices from every corner of the globe, ensuring over 95,000 students receive a world-class learning experience from Kindergarten to Year 13. In 28 countries, Inspired schools are individually developed and anchored in the vibrant cultures of their respective locations. They collectively form an international family of schools that nurtures each student's academic and personal development in a progressive, dynamic, and innovative learning environment.

• Design & Develop Agentic Systems: Build intelligent agents capable of autonomous planning, reasoning, and task execution, often using LLMs (e.g., GPT-class, LLaMA), multi-modal models, and autonomous workflows • Orchestration & Frameworks: Implement agent orchestration using frameworks like LangChain, AutoGen, CrewAI, Semantic Kernel, or custom solutions • Retrieval-Augmented Generation (RAG): Design and optimize RAG pipelines for enhanced reasoning with external knowledge, including document ingestion, chunking, embeddings, vector stores, and retrieval ranking • Tool & Memory Integration: Develop agents that call APIs, databases, and other tools, maintain memory, and adapt based on outcomes • Evaluation & Monitoring: Create evaluation frameworks for accuracy, grounding, latency, and cost; build observability for agent behavior and failure modes • Model Adaptation: Fine-tune or adapt foundation models (e.g., via LoRA, adapters) for domain-specific use cases • Production Deployment: Deploy GenAI/agentic systems in cloud-native environments with CI/CD, versioning, and runtime safeguards • Cross-Functional Collaboration: Work with data scientists, ML engineers, product teams, and governance/compliance stakeholders

• Build, test, and deploy autonomous, multi-agent systems using frameworks such as AutoGen and LangGraph. • Engineer robust data ingestion pipelines capable of processing complex, multi-modal healthcare data. • Design and execute prompt engineering strategies. • Partner with data scientists, product managers, and cloud engineers to transition AI models into high-concurrency production environments. • Build and maintain MLOps pipelines, ensuring secure containerization, CI/CD integration, and comprehensive system telemetry in adherence to healthcare privacy regulations (HIPAA, HITRUST).