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The consultant will lead end-to-end implementation of AI security solutions and provide technical guidance to customers to ensure successful AI risk management and data protection. They will also serve as a subject matter expert, influencing product roadmaps and developing internal knowledge sharing materials.
The AI Architect will drive the innovation, roadmap, and technical implementation of agentic AI solutions within the ServiceNow platform. They will provide technical advisory, lead enablement programs, and partner with cross-functional teams to ensure successful AI adoption and value realization.
You will manage a portfolio of strategic AI-native customers, serving as a trusted advisor to executive and technical leaders. You will drive complex enterprise sales cycles while collaborating across internal teams to accelerate adoption of the Elastic Search AI Platform.
Design and build backend systems powered by LLMs and develop agent workflows with tool integrations. Manage RAG pipelines, prompt orchestration, and optimize performance for production AI features.
The AI Solutions Architect leads the technical execution of AI initiatives by selecting, building, and integrating agentic AI tools into the company's existing stack. They collaborate with cross-functional teams to ensure solutions are secure, scalable, and effectively adopted by staff.
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The Staff Applied AI Engineer will architect and develop backend systems, APIs, and agents that integrate foundational AI models into the company's technology stack. This role involves driving test-and-learn experiments and collaborating with cross-functional teams to translate business needs into scalable AI-powered solutions.
The Staff Applied AI Engineer will architect and develop backend systems, APIs, and agents that integrate foundational AI models into the company's technology stack. They will drive test-and-learn experiments and build scalable infrastructure to support AI-powered solutions and business automation.
The intern will contribute to the co-design of next-generation CPU and GPU architectures by developing compiler innovations for AI/ML model optimizations. They will analyze AI model performance data and evaluate the impact of hardware and software optimizations on workload efficiency.
The Senior Principal AI Business Partner shapes AI investment, portfolio prioritization, and delivery standards across business units. They act as a strategic advisor to executive sponsors, framing complex AI problems and overseeing the design and execution of enterprise-scale AI solutions.
The Senior Technical Product Manager leads the strategy, development, and adoption of customer-facing and internal APIs and AI-enabled capabilities. This role manages cross-functional delivery teams to translate business needs into secure, scalable technical solutions.
The SEO AI Specialist will own organic search strategy, focusing on optimizing client content for AI-driven search surfaces like AI Overviews and LLMs. They will also conduct technical SEO audits, manage keyword strategy, and monitor performance using industry-standard analytics tools.
You will lead the development and maintenance of a secure AI-driven pipeline, establishing the conventions, gates, and autonomy tiers for AI-generated code. The role involves owning the knowledge plane, implementing verification gates, and continuously calibrating the system based on incident history and performance metrics.
You will lead the strategy for AI-driven analytics and reporting while evolving the data architecture to support these advanced use cases. This role involves mentoring the analytics team and ensuring data models are optimized for both human analysts and AI agents.
You will design, develop, and deploy intelligent business solutions by combining Microsoft Power Platform with Generative AI technologies. You will work within multidisciplinary teams to build scalable, secure, and user-centric digital solutions that drive business transformation.
The Lead Director will establish and lead the enterprise-wide AI FinOps capability, defining the strategy, governance, and financial frameworks for AI investments. They will partner with cross-functional teams to provide transparency into AI spending and ensure value realization across the organization.
The Senior Account Manager will drive NVIDIA's relationships with AI-native startups and scaleups to accelerate their adoption of NVIDIA AI technology. This role involves leading cross-functional teams to deliver high-value solutions and representing NVIDIA within the broader AI ecosystem.
You will lead the architecture and development of a multi-RAT digital twin for Open RAN solutions, integrating production software into closed-loop simulations. Additionally, you will design fidelity models and leverage AI/ML to optimize RAN performance, ensuring simulation accuracy and scalability.
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You will architect and operate a secure, scalable local LLM platform to support engineering and business workflows. This involves building inference gateways, RAG pipelines, and observability tools while ensuring data security and model performance.
The AI Scientist will bridge applied research and production engineering to design and ship advanced machine learning systems. This role involves managing the full lifecycle of AI projects from problem framing and experimentation to deployment and continuous improvement.
The AI Optimization Engineer will focus on maximizing throughput, minimizing latency, and reducing costs for large neural network training and inference workloads. They will collaborate with cross-functional teams to translate requirements into high-performance solutions while mentoring junior engineers.
The AI Prompt Designer will lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures. This role involves building reusable design patterns and evaluation frameworks that scale across various organizational teams and use cases.
The Generative AI Engineer will design, execute, and operationalize fine-tuning workflows for large language models using various learning approaches. They will collaborate with cross-functional teams to translate requirements into production-grade solutions while mentoring junior engineers.
You will conduct AI red teaming security assessments for enterprise clients and develop novel testing methodologies for emerging AI modalities. Additionally, you will build automated tools to scale security services and present actionable findings to technical and executive stakeholders.
You will design and execute experiments to evaluate the reliability and capability of AI agents, turning research findings into actionable product decisions. Additionally, you will build evaluation layers and prototype research concepts into functional product features.
The AI Security Engineer will lead the design and implementation of security controls, threat models, and incident response strategies for AI and machine learning systems. They will also secure training pipelines, conduct red-team exercises, and ensure compliance with regulatory obligations.
The Edge AI Engineer will design, optimize, and deploy machine learning models for resource-constrained edge devices such as mobile platforms and embedded systems. They will also build cross-platform inference runtimes and implement on-device model update workflows to ensure reliable performance in production environments.
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Build and deploy artificial intelligence agents and intelligent applications that solve real customer and business challenges. Design, develop, and maintain scalable backend services and APIs that power AI-driven experiences.
This role is split between managing accounting engagements for a portfolio of clients and leading firm-wide AI and workflow innovation initiatives. You will be responsible for financial reporting, budgeting, and the strategic deployment of AI tools to optimize service delivery.
Manage the end-to-end delivery of enterprise AI engagements by coordinating project plans, milestones, and cross-functional teams. Serve as the primary point of contact for customers while identifying risks and driving technical solutions to completion.
Maintain and extend backend systems for an AI-powered research platform while building optimized data ingestion pipelines. Collaborate with cross-functional teams to integrate LLMs and agents into production workflows.
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