• Architect, design and deliver robust implementable solutions for complex supply chain requirements using SAP IBP Supply Planning, Demand Planning, Optimization and Fulfillment Techniques involving SAP IBP utilizing both order-series and time-series planning. • Demonstrate process improvement techniques to streamline business process and architect solutions. • Lead projects to implement new and improved existing functionalities that are already implemented at NVIDIA in IBP. • Build prototypes and proof of concepts for business requirements and translate them into effective operational solutions. • Apply industry-best practices for data analysis and share across the teams. • Build business and product scenarios to help the BU improve NVIDIA's profitability and market share. • Perform testing to support system implementations and upgrades, and drive system design analysis, testing, and training • Collaborate with cross functional teams in business and IT to deliver comprehensive supply chain planning solutions, and Influence senior leadership in business to adopt scalable solutions and systems/tools.

Role Description As the Senior AI Ops Engineer, you will lead the advancement of our AI capabilities, focusing on engineering excellence and leveraging generative AI to enhance our end-to-end operations from experimentation to deployment. Your role will involve driving research and development in analytical techniques, creating new AI-driven products, and mentoring junior talent. With our infrastructure transitioning to Oracle Cloud Infrastructure (OCI), you will play a pivotal role in architecting, optimizing, and scaling AI workloads within OCI’s ecosystem. Join us in transforming the healthcare landscape! Job Roles and Responsibilities - Enhance AI Operations - Utilize generative AI to streamline processes and tools, enabling faster and more effective development and deployment. - Build scalable GenAI infrastructure with Terraform, Docker, Helm, and Kubernetes (OKE, AKS, and OCI-native services such as OCI Data Science, OCI AI Infrastructure, and OCI Streaming). - Architect hybrid AI systems across OCI, Azure, and on-prem GPU clusters, ensuring seamless data and model orchestration. - Automate model pipelines (training → fine-tuning → inference) using Jenkins, GitHub Actions, and MLflow integrated with OCI Object Storage and OCI DevOps. - Serve multimodal LLMs with vLLM, Triton, and Streamlit dashboards deployed on OCI Container Engine for Kubernetes (OKE) and optimized for OCI GPUs. - Deploy secure RAG-based microservices backed by Vector DBs, Databricks, and OCI AI Services (e.g., Data Labeling, Generative AI APIs) and private LLM gateways. - Lead R&D Efforts - Drive research and development using generative AI to create reusable code components and establish best practices for OCI-based MLOps and AI infrastructure. - Stakeholder Collaboration - Partner with stakeholders to identify opportunities for new AI-driven products through data insights, leveraging OCI’s data and analytics stack (Autonomous Data Warehouse, Data Flow, Data Integration). - Program-Level Initiatives - Lead initiatives focused on the initial development of AI-powered products that utilize OCI-native AI and ML services for scalability and compliance. - Ethical AI/ML Practices - Ensure AI models are transparent, relevant, and ethically used across all environments, maintaining consistency between OCI and multi-cloud systems. - Team Management - Mentor and develop junior data scientists and engineers, fostering a culture of continuous learning and innovation in OCI and multi-cloud AI engineering. - Compliance - Ensure adherence to HIPAA regulations and data privacy standards: HIPAA, SOC2, BAA enforcement, and PHI-safe model routing within OCI’s secure architecture. Qualifications - Must have 7+ years in Data Science, 3+ years in R&D, 2+ years mentoring/managing junior engineers. - Deep expertise in Kubernetes, CI/CD, LLMOps, and cloud-native architecture. - Exposure to taking AI agents from concept to compliance-ready production is preferred. - Strong ML Infra experience with hands-on Terraform/K8s/IaC. - Deep experience with LLMOps, model versioning, and hybrid GPU deployment. - Must have fluency in Python, Bash, and container-native toolchains. - Familiarity with open-weight LLMs (Mistral, Grok, LLaVA, etc.). - Passion for building AI that’s not just powerful, but secure and compliant. - Experience in dealing with Peta Bytes of data. - Strong problem-solving, critical thinking, creativity, organizational, and communication skills. Preferred Experience - Healthcare and process optimization. - Bachelor's in Quantitative Science; Master's or PhD preferred. Compensation The salary range for this position is $170K to $180K. Specific offers take into account a candidate’s education, experience and skills, as well as the candidate’s work location and internal equity. This position is also eligible for health insurance, 401k and bonus opportunity. Benefits - Medical, dental and vision coverage with low deductible & copay. - Life insurance. - Short and long-term disability. - Paid Parental Leave. - 401(k) + match. - Employee Stock Purchase Plan. - Generous Paid Time Off – accrued based on years of service. - 10 paid company holidays. - Tuition reimbursement. - Flexible Spending Account. - Employee Assistance Program. - Sick time benefits – for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year. EEO Statement Claritev is an Equal Opportunity Employer and complies with all applicable laws and regulations. Qualified applicants will receive consideration for employment without regard to age, race, color, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status. Application Deadline We will generally accept applications for at least 5 calendar days from the posting date or as long as the job remains posted.

• Manage and coordinate all technical aspects of the project including planning, design, development, testing, and deployment. • Develop and execute system build plans accounting for software architecture, information security, and hardware deployment. • Work with the Project Manager and provide technical input into the overall project schedule, budget, resource requirements, and risk management. • Lead engineering workshops on topics such as system design, data conversion, business process reviews, test, and validation planning, and change management. • Installation and configuration of OSI monarch advanced distribution management applications. • Design and configure SCADA/GMS/EMS/ADMS/OMS systems to meet the specific needs of our clients. • Deploy and integrate SCADA/GMS/EMS/ADMS/OMS systems with other equipment and software. • Provide training and support to clients during and after the implementation process. • Collaborate with project teams and other stakeholders to ensure successful implementation of the project. • Perform system and acceptance testing with the end customers. • Test and validate system configurations to ensure they meet client requirements and industry standards including NERC CIP. • Develop scripts and other solutions to integrate 3rd party systems. • Identify and troubleshoot any issues that arise during the implementation process. • Keep up to date with the latest developments in the field and ensure systems are implemented in accordance with industry best practices. • Travel to customer sites and work directly with customers to successfully deliver, test, and integrate systems. • Contribute to proposals, work plans, budgets, and schedules for services opportunities.

• Lead customer conversations in English with confidence and clarity, translating mission needs into crisp technical requirements and clear next steps. • Deeply understand Loft Orbital’s technical solution ecosystem, including satellite platforms, in-orbit capabilities, mission services, and operations to communicate and discuss mission solutions, accommodations, and design tradeoffs concisely to both customers and engineers. • Evaluate customer design and interface requirements for physical and on-demand missions, aligning with Loft’s program offerings and technical specifications. • Drive the development of customer-specific technical solutions, asking the right questions throughout the sales process to align on program expectations. • Own technical proposal content end-to-end, including preliminary architectures, mission analyses, and written narratives that are structured, clear, and mission-oriented. • Act as the primary coordination point between Business Development and Engineering—analyzing customer requirements, synthesizing information, building alignment, and pushing discussions to outcomes rather than open-ended exploration.