• Serve as EnerSys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes. • Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap aligned with growth, productivity, quality, safety, and risk objectives. • Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications. • Represent EnerSys externally with strategic AI partners, technology providers, and industry forums. • Design, implement, and continuously evolve the enterprise AI operating model, including governance forums, funding and intake processes, prioritization methods, and decision rights. • Chair and run the Executive AI Steering Committee, ensuring disciplined decision making, clear accountability, and execution follow through; set agendas, align key stakeholders, and communicate decisions and actions clearly. • Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management in partnership with Legal, Cybersecurity, IT Architecture, HR, and Compliance. • Own AI investment governance, ensuring alignment with capital planning, transformation funding, and enterprise portfolio priorities. • Own the global AI use case portfolio and prioritization framework, balancing short term value delivery with long term strategic capability building. • Ensure AI initiatives progress efficiently from ideation to pilot to scaled production—eliminating “pilot only” stagnation. • Define, track, and report enterprise AI value metrics, including operational efficiency, cost reduction, quality improvement, risk mitigation, revenue enablement, and customer impact. • Regularly recalibrate the AI roadmap based on realized outcomes, business performance, and evolving priorities. • Orchestrate cross-functional delivery across IT, data, digital platforms, business units, and external partners—creating shared plans, clear ownership, and fast decisions. • Resolve enterprise level dependencies and escalations impacting delivery, adoption, or value realization by facilitating trade-off discussions, aligning decision makers, and driving timely, documented outcomes. • Ensure AI initiatives are integrated with core enterprise platforms (ERP, data environment, digital products) rather than delivered as isolated solutions. • Build scalable execution playbooks, delivery standards, and reusable components to accelerate adoption across regions and functions. • Partner with HR and Communications to lead enterprise-wide change management, AI literacy, and workforce enablement. • Sponsor AI capability building, including training programs, citizen developer models, communities of practice, and leadership education. • Drive cultural adoption by positioning AI as a core business capability embedded in how work gets done—not as a technology experiment. • Support workforce transformation planning, including role evolution, ethical considerations, and future skills development. • Build, lead, and develop a high performing enterprise AI organization with clear roles, succession, and career paths. • Set performance expectations, accountability, and development plans for direct and indirect reports. • Foster a strong culture of accountability, collaboration, and execution discipline across the AI ecosystem.

Role Description We are seeking an Applied AI/ML Scientist that will be responsible for developing and deploying machine learning models that solve complex, real-world scientific and industrial challenges. In this role, you will combine advanced AI/ML approaches with your energy sector expertise to build models that solve complex industrial problems, optimize processes, and drive real-world breakthroughs. You will work closely with domain experts, product teams, and engineers to translate scientific problems into scalable AI solutions that drive measurable business and customer impact. If you have a passion for solving industry challenges with real impact, let’s talk! Join us in building a more sustainable world through the power of AI and scientific innovation. Key Responsibilities - Design, develop, and deploy machine learning and deep learning models for scientific applications (e.g., materials discovery, chemical modeling, process optimization) - Translate complex scientific and business problems into tractable AI/ML frameworks - Work with real-world structured and unstructured scientific data (e.g., experimental, simulation, and literature data) - Build and maintain data pipelines, feature engineering workflows, and model evaluation frameworks - Collaborate cross-functionally with scientists, engineers, and product managers to deliver production-ready solutions - Partner closely with Customer Success and client-facing teams to understand customer needs, translate requirements into AI/ML solutions, and support the successful deployment, adoption, and ongoing optimization of models in customer environments - Apply techniques such as supervised/unsupervised learning, generative models, and optimization algorithms - Contribute to the integration of models into scalable software platforms and APIs - Stay current with advancements in AI/ML and relevant scientific domains; evaluate and apply new methods where appropriate - Perform strategic research oriented towards improving NobleAI’s core technology - Communicate findings and model outputs clearly to both technical and non-technical stakeholders - Periodic travel to customer sites and attend industry events Qualifications - Ph.D. in Geoscience, Geophysics, Production Engineering, Reservoir Engineering, or other Energy-related quantitative discipline - Degree or coursework in Machine Learning - Hands-on experience applying machine learning to real-world problems in science and engineering - Strong background in machine learning: classical and deep learning techniques (examples may include CNNs, transformers, or embedding techniques, etc.), focus on supervised learning - Strong experience in Python and associated ML frameworks (Pytorch, Tensorflow, Keras, sklearn, etc.) - Demonstrated ability to effectively communicate complex technical details at a high level - Solid understanding of statistical modeling, optimization, and algorithm design - Proven ability to deploy models into production environments Preferred - Experience in either Natural Language Processing, Computer Vision, uncertainty quantification, or unsupervised learning approaches - Experience with cloud or distributed training frameworks (Azure, AWS, GCP) and MLOps practices - Experience in scientific domains such as chemistry, materials science, or energy - Familiarity with physics-informed ML, geological/reservoir modeling, and/or production forecasting and flow assurance optimization - Experience with generative AI methods (e.g., diffusion models, transformers) applied to scientific problems Benefits - Top-tier health benefits coverage, including medical, dental, vision, disability and life insurance - Flexible Paid Time Off & generous Holidays - Remote-first with optional co-working access at The Ion for our Houston-based employees - 401(k) with employer match - Equity package - Base Salary Range $190k - $220k (Depending on experience & Geographic location) - Performance-based bonus plan

Vice President, Enterprise AI Strategy and Transformation (Remote) USA - Remote time type Full time CrowdStrike is the industry-defining cybersecurity company. We are on a trajectory to $10B in revenue and beyond, and we are betting on Enterprise AI to supercharge that journey.   We are seeking a visionary Vice President to architect and lead our AI Center of Excellence (CoE). This is not a theoretical role; it is an operational leadership position tasked with deploying the next generation of agentic systems and AI-driven workflows across our entire enterprise. You will bridge the gap between technical possibility and business reality, translating complex AI capabilities into scalable solutions that drive GTM velocity, R&D innovation, and operational efficiency.   You will be the internal champion for our "AI-First" ambition, ensuring that every CrowdStriker—from HR to Sales to Engineering—is empowered by secure, resilient, and responsible AI.   What You'll Do: Strategic Leadership & Governance - Define the Enterprise AI Roadmap: Own the company-wide internal strategy for AI platforms, tools, and capabilities. Align AI initiatives directly with the $10B revenue goal and OPEX optimization targets. - Lead the AI Center of Excellence: Build and manage a high-performing cross-functional team (Product Managers, Engineers, Analysts) to serve as the engine of AI transformation. - Executive Leadership: Chair the AI SteerCo, driving prioritization, investment strategy, and buy-vs-build decisions with the C-Suite and executive leadership. - Governance & Ethics: Develop rigorous frameworks for AI governance, compliance, and risk management. Ensure all internal AI adoption aligns with CrowdStrike’s standards for security and responsibility. Execution & Transformation - Transform through the coordinated deployment of agentic systems: Enable implementation of intelligent, autonomous workflows that redefine operational models across the enterprise. - Cross-Enterprise Integration: Partner with functional business teams to embed AI into their daily operations, ensuring seamless integration into existing enterprise applications. - Drive Productivity Step-Change: Identify and align teams to execute on opportunities to bend the OPEX growth curve with a focus on hyper-automation and process re-engineering. - Innovation Scouting: Continuously assess the emerging technology landscape (Generative AI, LLMs, Autonomous Agents) to keep CrowdStrike at the forefront of internal innovation.   The Candidate Profile We are looking for a rare hybrid: a strategist with the soul of a technologist, and a technologist with the polish of a management consultant. What You'll Need: - Executive Gravity: 15+ years of experience, with a proven track record of leading enterprise-wide transformation initiatives in high-growth, large-scale organizations. - AI Fluency: Deep understanding of the current AI landscape, specifically Generative AI, agentic capabilities, and Large Language Models (LLMs). You know the difference between hype and high-impact utility. - Strong Executive Leadership: Demonstrated ability to lead executive-level steering committees, influence C-level decision-making, and secure investment for technology initiatives. - Technical Leadership: Experience managing technical teams (Data Science, Engineering) and partnering with Product Engineering organizations. - Operational Rigor: Strong background in business process automation. You understand the ecosystems of CRM, ERP, and Enterprise Data Lakes and how to modernize them. Preferred Attributes: - Consulting DNA: Background in top-tier management consulting, with expertise in operational efficiency and digital strategy. - Governance Expertise: Experience developing AI ethics policies, risk assessments, and regulatory compliance frameworks. - "Customer Zero" Mindset: Experience implementing a company’s own technology internally to drive product feedback loops. CrowdStrike, Inc. is committed to equal pay for equal work in its compensation practices. The base salary range for this position in the U.S. is $300,000.00 - $340,000.00 per year + variable/incentive compensation + equity + benefits. A candidate's salary is determined by various factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location   Benefits of Working at CrowdStrike: - Market leader in compensation and equity awards - Comprehensive physical and mental wellness programs  - Competitive vacation and holidays for recharge   - Paid parental and adoption leaves - Professional development opportunities for all employees regardless of level or role - Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections - Vibrant office culture with world class amenities - Great Place to Work Certified™ across the globe

Role Description We are seeking a Principal AI Architect – Generative AI & NLP to lead the design and deployment of next-generation AI platforms powering intelligent customer experiences. This role will drive innovation across LLM-based conversational AI, agent assist systems, and autonomous CX workflows, enabling scalable, secure, and human-like interactions across global enterprises. You will play a critical role in shaping the future of AI-driven contact center platforms, combining Generative AI, GraphRAG, RLHF, and multi-agent systems to deliver highly personalized, context-aware, and trustworthy customer interactions. Qualifications - 15+ years of experience in AI/ML, NLP, or distributed systems - 5+ years working with Generative AI and LLM-based systems - Proven experience building production-grade AI platforms at scale - Deep expertise in: - GraphRAG architecture (not just RAG) - RLHF and alignment systems - Multi-agent AI systems - Distributed training and inference - Strong programming skills in Python, Scala, or Java - Experience with PyTorch, TensorFlow, Transformers Requirements - Define and lead the architecture of enterprise-scale LLM-driven conversational AI platforms - Design advanced RAG and GraphRAG-based knowledge systems for customer support and agent assist - Architect low-latency, high-throughput inference systems for real-time interactions - Build and optimize LLM pipelines, including fine-tuning (LoRA, QLoRA) and prompt orchestration - Develop multi-agent AI systems for autonomous customer workflows and decision intelligence - Implement semantic search, hybrid retrieval, and contextual reasoning systems - Design multimodal AI capabilities (text, voice, chat) - Develop and deploy RLHF pipelines, guardrails, and hallucination mitigation frameworks - Establish Responsible AI practices, including fairness, explainability, and compliance - Lead AI governance frameworks for enterprise deployments - Architect distributed training and inference pipelines across GPU clusters - Optimize model performance using quantization, mixed precision (FP16/BF16), and MoE architectures - Reduce latency and cost using frameworks like vLLM, Triton, Ray - Lead and mentor teams of AI engineers, researchers, and architects - Collaborate with product, engineering, and CX teams to deliver AI-powered solutions - Partner with enterprise clients to design and deploy custom AI solutions for contact centers Benefits - Work on cutting-edge AI problems at the intersection of Generative AI and customer experience - Build autonomous AI agents that transform how businesses interact with customers - Lead innovation in GraphRAG and real-time conversational intelligence - Directly impact millions of customer interactions globally Company Description All your information will be kept confidential according to EEO guidelines.