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The Content Writer will create engaging internal-facing content, collaborate with teams to ensure consistent messaging, and analyze content performance to optimize marketing strategies. Responsibilities include producing case studies, one-pagers, and thought leadership articles to enhance customer engagement.

The Consultant will work with clients to develop strategies and programs leveraging data and technology, manage project delivery, and collaborate with senior team members. Responsibilities include problem-solving, client relationship management, and contributing to intellectual capital.

The Head of Product Operations will strategize and execute product planning, enhance operational excellence, and communicate effectively across teams while leading special projects and building a strong culture in the Chicago tech hub.

Lead internal AI training and solution development across Grainger's corporate and business functions, advising leaders on AI integration and impact. Design prototypes and drive functionality while collaborating with technical teams.

The Senior Data Engineer will develop and maintain data pipelines and products, collaborating with various teams to integrate data sources for analytics and reporting.

Design and maintain databases, monitor performance, provide support and develop documentation for database solutions. Participate in project phases and disaster recovery drills.

The Senior Wealth Management Lending Specialist will drive business development by building relationships, educating advisors, and providing consultative solutions in securities-based lending.

Build and maintain AI-driven backend services and APIs, integrate LLM providers (OpenAI, Anthropic), implement scalable systems using Postgres and Redis, design Pydantic data models, write tests, troubleshoot performance, and collaborate on deployment and platform improvements.

The Senior Marketing Operations Manager will oversee marketing automation, lead management, and segmentation while optimizing revenue systems and ensuring data integrity.

The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.

As a strategic product manager, lead digital customer engagement initiatives, integrating CRM platforms and data-driven solutions to enhance client outcomes in life sciences.

The Governance & Risk Analyst will manage third-party risk assessments, collaborate with stakeholders on risk remediation, and support governance processes. Responsibilities include conducting vendor risk assessments, documenting findings, and maintaining risk registers.

As a Senior Cloud Security Engineer, you'll enhance cloud security through risk assessment, vulnerability management, secure architecture design, and automation in cloud environments, notably AWS and GCP.

The Principal I, Strategic AI Sales will drive business growth for Braze AI by managing customer relationships, collaborating with sales, and training teams on AI decision-making applications.

As a Senior Platform Software Engineer, you will build and maintain Braze's internal infrastructure as a service platform, collaborate with engineering teams, develop frameworks for large-scale distributed processing, manage incidents, and automate operational tasks.

As a Marketing Science Partner, you will analyze marketing data, develop optimization methods, drive product adoption, and lead customer insights initiatives.

The Amazon DSP Specialist will lead campaign execution for DSP clients, manage live campaigns, and develop SOPs while training the Smart Services team.

As a Software Engineer, you will build AI systems to enhance developer workflows, implementing agents and servers, and ensuring code reliability through evaluation pipelines.

The role involves advising on cryptocurrency regulations, drafting agreements, ensuring compliance, and collaborating with teams to mitigate legal risks.

The Machine Learning Engineer will develop and optimize large-scale ML models, build low-latency inference pipelines, and collaborate with teams to enhance performance and automate ML processes.