• Complete onboarding, gaining familiarity with our enterprise systems and ongoing AI initiatives • Provide feedback on your onboarding experience, embodying our value of continuous improvement • Build relationships across various departments to understand their unique challenges and AI opportunities • Gain a basic understanding of our business operations and how AI can enhance productivity • Develop prototypes and proof-of-concepts for AI-powered features that can boost employee productivity and creativity • Assist in fine-tuning and optimizing LLMs for specific enterprise use cases (e.g., report writing, data analysis, creative ideation) • Contribute to the development of prompt engineering strategies for various business applications • Participate in creating AI-driven tools that can be integrated into our existing workflow systems • Collaborate on AI model integration projects, ensuring seamless user experiences across different platforms • Assist in evaluating and benchmarking AI model performance against business KPIs and user satisfaction metrics • Present your work and findings to stakeholders, translating complex AI concepts for both technical and non-technical audiences

Company Description Veza is the pioneer in identity security, purpose-built to answer the fundamental question enterprises face: who can and should take what action on what data. Veza's Access Graph platform maps an organization's entire identity ecosystem across users, groups, roles, policies, permissions, and resources providing deep visibility and control over human, non-human, and agentic identities across SaaS, cloud, on-prem, and custom applications. With over 30 billion access permissions under management, global enterprises including Blackstone, Expedia, and Wynn Resorts trust Veza to manage privileged access monitoring, non-human identity security, access entitlement management, and next-generation identity governance. Founded in 2020 and headquartered in Redwood City, California, Veza is now part of the ServiceNow family, with the acquisition closing in March 2026. The combination brings together Veza's AI-native Access Graph with ServiceNow's AI Control Tower and agentic workflows, enabling organizations to enforce end-to-end identity security rooted in the principle of least privilege across applications, data, cloud environments, and AI agents. For engineers joining Veza today, this means the scale and resources of an enterprise platform company, with the product velocity and mission-driven focus of a security innovator at a pivotal moment in the industry. Job Description We are seeking a Senior Staff Software Engineer to serve as the technical visionary and architect for our multi-agent harness platform, and writing agents for our products. This is a high-leverage, tier-one leadership opportunity operating at the absolute frontier of Agent research and large-scale backend systems engineering. In this role, you won't just implement agents-you will define the architectural patterns, scalability guardrails, and strategic direction for how intelligent, autonomous agents reason, decide, and secure the modern enterprise. What You Will Do - Architect & Vision: Define the technical roadmap and architecture for Access AI Platform, ensuring high availability, low latency, and deterministic reliability. - System Design: Lead the design of advanced agent orchestration layers, multi-agent communication, and sophisticated context/memory management. - Productionize at Scale: Transition cutting-edge LLM capabilities and MCP frameworks from experimental prototypes into hardened, enterprise-grade pipelines within our identity access infrastructure. - Technical Leadership: Act as a force multiplier across the engineering organization. Define engineering excellence, establish robust test/evaluation frameworks for non-deterministic AI systems, and mentor senior and staff-level engineers. - Cross-Functional Influence: Partner closely with Product, Security, and Executive leadership to align technical investments with long-term business strategy, pioneering new capabilities from ideation to global deployment. Qualifications What You Bring - Education: Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related technical field. - Experience: * 10+ years of professional software engineering experience, with a proven track record of technical leadership at a Staff or Senior Staff level. - 2+ years of hands-on experience in architectural design and production deployment of GenAI technologies, multi-agent systems, LLM orchestration frameworks (e.g., LangChain, AutoGen), or Model Context Protocols (MCP). - Technical Mastery: * Expert-level proficiency in Python and Golang (or Java), with deep expertise in distributed systems, microservices architectures, and high-throughput API design. - Deep understanding of Cloud Platforms (AWS, Azure, GCP) with experience designing or integrating with enterprise Identity and Access Management (IAM) environments and security fabrics. - Execution & Ownership: A strong sense of product ownership. You have a history of taking ambiguous, 0-to-1 AI initiatives and scaling them to 1-to-100 enterprise realities. - Communication: Exceptional communication skills with a demonstrated ability to distill complex AI reasoning and architectural trade-offs into clear, strategic narratives for both engineering teams and executive boardrooms. For positions in this location, we offer a base pay of $171,900 - $300,800, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Role Description The Senior AI Engineer is responsible for designing, building, scaling, and optimizing production-grade Agentic AI systems that drive measurable business outcomes across The Home Depot. Operating at the intersection of Data Science, Machine Learning Engineering, and Software Engineering, this hands-on role translates AI concepts into enterprise-ready products. This role involves developing scalable applications powered by LLMs, SLMs, Retrieval-Augmented Generation (RAG) frameworks, and autonomous agents. You will build the core orchestration layers for multi-agent workflows, tool integration, and planning, alongside the infrastructure required for reliable, large-scale cloud deployment. By partnering with product, engineering, and business teams, you will rapidly prototype solutions, navigate ambiguity, and seamlessly transition cutting-edge AI capabilities from concept to production. Qualifications - 6+ years of experience in AI, Machine Learning Engineering, or Software Engineering with strong Python development skills and modern software engineering practices. - Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems. - Deep understanding of AI/ML foundations, including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases. - Experience developing orchestration layers (task execution, routing, planning, workflows) and seamlessly integrating AI solutions with enterprise platforms, APIs, and business systems. - Expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (e.g., Terraform), and AI pipeline design. - Hands-on implementation of MLOps/LLMOps best practices (CI/CD, automated testing, model versioning and registries, governance, compliance, and security) across the full AI/agent lifecycle. - Experience building automated CI/CD pipelines for AI/agentic systems, implementing progressive rollout strategies (canary, blue-green, and shadow deployments) with automated rollback. - Establishing end-to-end observability (logging, metrics, distributed tracing, and automated alerting) across models, agents, and orchestration layers to ensure production reliability, performance, and cost/token efficiency at scale. - Demonstrated ability to optimize complex AI systems for performance, reliability, scalability, latency, cost efficiency, and token use, as well as debugging operational failure modes. - Excellent cross-functional communication and collaboration skills, with a proven ability to take AI solutions from concept to production in complex enterprise environments. Requirements - Typically requires overnight travel 5% to 20% of the time. - Most of the time is spent sitting in a comfortable position with frequent opportunities to move about. - Located in a comfortable indoor area with infrequent and non-objectionable unpleasant conditions. Benefits - Health care benefits - 401K - ESPP - Paid time off - Success sharing bonus Company Description For a full list of the various benefits The Home Depot offers, visit The Home Depot Benefits . For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents: The pay range for this position is between $100,000.00 - $180,000.00.

Role Description The AI/ML Delivery Engineer is a hands-on senior practitioner who designs, builds, and scales enterprise AI, ML, and data products across cloud environments. This role combines deep engineering expertise with solution architecture, delivery leadership, and executive-level communication. This role supports the NIH mission by delivering secure, scalable, and innovative AI and data solutions that accelerate biomedical research, improve operational efficiency, and enable data-driven decision-making to advance human health. MEANINGFUL WORK AND PERSONAL IMPACT - The ideal candidate can move from strategy to production implementation across intelligent search, generative AI chat, agentic workflows, predictive ML, computer vision, and medical AI imaging. - They bridge data science, software engineering, platform engineering, and security to deliver robust, governed, cost-aware, fit-for-mission AI solutions. Solution Design and Delivery - Architect and deliver end-to-end AI/ML and generative AI solutions across the full lifecycle, including data integration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. - Design scalable, secure, and governed AI/ML architectures that support enterprise data management, cloud-native services, distributed computing, and high-performance workloads. - Develop and deploy production-ready AI solutions using modern techniques for large language models, intelligent search, workflow automation, model evaluation, monitoring, and continuous optimization. - Integrate enterprise AI and cloud services with organizational data platforms, security controls, governance frameworks, and operational processes. - Deliver AI and machine learning solutions across a variety of domains, including natural language processing, computer vision, predictive analytics, intelligent search, multimodal AI, and other mission-focused applications, using industry-standard frameworks and tools. - Design secure application programming interfaces (APIs), integration services, data pipelines, and orchestration workflows that enable AI capabilities to be reliably consumed by enterprise systems and end users. Technical Leadership, Governance, and Delivery Excellence - Serve as the AI/ML technical authority for cross-functional data science, engineering, platform, security, infrastructure, and business teams. - Lead architecture reviews, AI readiness assessments, performance benchmarking, and infrastructure trade-off analysis for large-scale cloud, GPU, and distributed data workloads. - Establish MLOps, LLMOps, and ModelOps practices for CI/CD, experiment tracking, model registry, prompt/model versioning, automated testing, deployment promotion, rollback, drift/quality monitoring, lineage, and cost optimization. - Define responsible AI controls for privacy, IAM, key management, audit logging, PHI/PII handling, explainability, model cards, bias/risk assessment, human oversight, and agentic guardrails. - Mentor engineers and data scientists while communicating complex AI concepts through clear solution narratives, architecture diagrams, demonstrations, and executive-ready materials. - Support solutioning activities by shaping technical approaches, estimating delivery patterns, and contributing to client responses. Qualifications - Education: Master of Science in Computer Science, Information Technology, Engineering, Mathematics/Statistics, Bioinformatics, Data Science, or equivalent professional experience. - Experience: 10+ years of related experience. - Hands-on experience with modern enterprise data platforms and cloud-native data architectures, including distributed data processing, data governance, machine learning lifecycle management, and batch and streaming data pipelines. - Production experience developing, deploying, and supporting AI/ML and generative AI solutions, including intelligent search, large language model (LLM) applications, workflow automation, model serving, evaluation, monitoring, and continuous improvement. - Experience with modern machine learning and deep learning frameworks, libraries, and tools for developing, training, evaluating, and deploying AI/ML solutions. - Experience designing, deploying, and managing AI/ML solutions in one or more major cloud environments, including cloud-native AI services, identity and access management, networking, security, and infrastructure. - Experience working with large, complex, sensitive, or regulated datasets, including data integration, migration, quality management, analytics, visualization, and governance in government, healthcare, or other regulated environments. - Excellent written and verbal communication skills, with the ability to collaborate effectively with technical teams, business stakeholders, and executive leadership. - Security clearance level: Must be able to obtain a Tier 3 Public Trust. - Must be a US Person. Requirements - This position is fully remote; If selected, travel to NIH at applicant's expense will be required for onboarding. Benefits - Growth: AI-powered career tool that identifies career steps and learning opportunities. - Support: An internal mobility team focused on helping you achieve your career goals. - Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off. - Flexibility: Full-flex work week to own your priorities at work and at home. - Community: Award-winning culture of innovation and a military-friendly workplace.