Content Manager Jobs

THE OPPORTUNITY Dillard’s is seeking a Production Control / Technical Support Analyst to work the night shift at our Data Centers in Central Arkansas. You must be able to work a flexible schedule, which includes weekends, holidays, and after hours. This position's primary focus is assisting users of Dillard’s Information Technology services who are experiencing complex procedural or operational problems with IT applications, hardware, or services. It is also responsible for executing, monitoring, and resolving issues with batch processing. THE TEAM Night Shift Operations is responsible for closing the business day and starting the batch processes during the overnight hours, performing systems maintenance, monitoring the performance of the batch processes, and ensuring all company applications are available on time to start the next business day. They are also responsible for providing technical support to all Dillard locations that are still online when the evening shift starts and as those locations come online in the morning. WHAT YOU WILL DO Provide technical software, hardware, and network problem resolution to all IT resource users by performing question/problem diagnosis and guiding users through step-by-step solutions Must be able to function independently Handle phone and email support for moderate system or content issues Identify, resolve, and escalate issues when necessary Clearly communicate technical solutions in a user-friendly, professional manner Record interactions in our service ticket database Leverage AI to quickly review service ticket histories and problem descriptions to identify patterns in recurring inquiries, and draft clear, standardized resolution documentation for the service ticket database Occasionally assist other staff members and monitor open tickets to ensure timely and effective resolution Provide equipment upgrade and maintenance assistance to personnel at all Dill

At GWI we’re always looking for extraordinary people who thrive on making an impact. We think big to make an impact, we’re not afraid to ask why , and we always show respect . Those values are what got us where we are today, and they’re a big part of what we’re looking for in you. Right now we’re looking for candidates who are interested in working at GWI but haven't quite yet spotted the perfect role within the company. By taking a moment to submit your application and answer a few curated questions, you're not just applying for a job - you're becoming a part of our proactive talent community. This way, as soon as the right opportunity arises that aligns with your profile, you'll be among the first we reach out to. Who knows, it could be the start of something, well, extraordinary . Our benefits Great benefits make a big difference. Not just to employees, but to the whole vibe of a business. That’s why when you work for us, you’ll enjoy a full spectrum of generous perks, rewards and office benefits. Competitve annual leave (excluding bank holidays) and December holiday office closure days on top Flexitime Early finishes on Fridays (4:30pm weekly, and 1pm during summer) Work from Anywhere in the world - up to 15 days Hybrid home/office working Latest tech equipment + WFH office budget A genuine commitment to mental and physical health, with a range of content, tools, and perks to help you look after your wellbeing OneGWI - the team that focuses on D&I in the workplace And more! Who we are GWI was founded with the knowledge that understanding your audience is really important for business. When you know who you’re speaking to and why, you can create content and campaigns that stand out to the people that matter. Through our global online survey, we gather data on the behaviour and perceptions of consumers across the world. This provides businesses with deep, actionable insights on their audience, revealed from data they trust. It’s been going we

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As a small team, we’re all generalists that work across the full stack (built in Typescript end-to-end). We’re looking for experienced engineers that thrive in an environment of autonomy and individual responsibility to help us build the future of product development. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in the US and Europe. You can work from anywhere within these regions. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Work closely with founders and design to implement new concepts and ideas Build AI-powered functionality into the core of Linear Update our realtime collaborative content editor used across all internal surfaces Build new user-facing features with beautiful and scalable UI components Obsessively improve application performance Refine our software development processes to keep the team operating at high velocity What we're looking for 5+ years of experience building customer-facing products at a high-quality software company Strong React and TypeScript fundamentals, with experience across the full stack (Browser technologies, Node, GraphQL, PostgreSQL) Track record of driving complex, end-to-end features (not just incremental improvemen

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As a small team, we’re all generalists that work across the full stack (built in Typescript end-to-end). We’re looking for experienced engineers that thrive in an environment of autonomy and individual responsibility to help us build the future of product development. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in the US and Europe. You can work from anywhere within those regions. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build new user-facing features with everything from database models to GraphQL resolvers and UI components Optimize our data synchronization stack by applying better serialization protocols Add real-time collaborative editing to our content editor Improve performance by profiling and tweaking virtualized list rendering Add analytics, monitoring, and alerts to our service so that we can better respond to operational incidents Open-source any non-trivial innovations that come out of our work on the product Redefine best-in-class software development processes so that we can build a purpose-built product. What we're looking for 5+ years of experience building customer-facing products at a high-quality software company Strong React and Typ

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As a small team, we’re all generalists and constantly picking up new challenges. When it comes to code, we’re looking to work with experienced people who can pick a problem and solve it. We use TypeScript and build scalable systems so we can continuously make progress on a solid foundation. We don’t expect you to have a background in everything we use, but we do expect strong JavaScript fundamentals and a background working with React and TypeScript. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America and Europe. You can work from most timezones within these regions. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build new user-facing features with everything from database models to GraphQL resolvers and UI components Optimize our data synchronization stack by applying better serialization protocols Add real-time collaborative editing to our content editor Improve performance by profiling and tweaking virtualized list rendering Add analytics, monitoring, and alerts to our service so that we can better respond to operational incidents Open-source any non-trivial innovations that come out of our work on the product Redefine best-in-class software deve

Senior DevSecOps Software Engineer Company: The Boeing Company The Boeing Company has an exciting opportunity for a Senior DevSecOps Software Engineer to support the ADaPS organization in Huntsville, AL. ADaPS (an organization of over 100 software engineers) supports programs across the entire portfolio of Boeing products including Space Launch Systems (SLS) Upper Stage, Satellite Efforts, and Advanced Missile Defense efforts including Patriot Advanced Capability (PAC3). ADaPS specializes in implementing rapid prototyping and development programs using small, adaptable agile teams. Position Responsibilities: Oversees establishment and maintenance of modern software development environments, with formalized processes for development, implementation, integration, testing, documenting, and deploying software changes Works collaboratively with software engineering teams to deploy and operate systems Oversees development and maintenance of continuous integration / continuous delivery (CI/CD) pipelines Oversees automation and streamlining of operations and processes that support software testing, including script development as needed Builds and maintains tools for deployment, monitoring, and operations Communicates technical content to stakeholders Analyzes, plans, and executes mitigation strategies to prevent potential security risks, threats, and vulnerabilities Troubleshoots and resolves issues in development, testing, and production environments Supports software development and testing operations. Performs software research and trade studies Security Clearance: This position requires the ability to obtain a U.S. Se

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities and Tasks: Develop and refine CMP processes to deliver outstanding performance and yield. Collaborate with cross-functional teams to successfully implement process improvements. Conduct rigorous data analysis to determine the root cause of process variations and implement corrective actions. Ensure all processes strictly align with industry standards and safety regulations. AI Relevant Job Responsibilities: - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM,

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: The Celonis Context Model provides a real-time digital twin of enterprise operations, serving as the bridge between enterprise systems and AI. It captures how business actually flows across systems, giving organizations and AI agents the context needed to optimize complex workflows in real time. As an engineer on the Context Model Core team, you will shape the foundation powering the future of Enterprise AI and Process Intelligence. The Role: We are looking for a Full Stack Engineer to build the core capabilities to power the Celonis Context Model. In this role, you will build the next generation of user-facing tools and robust backend services that define how the world’s largest enterprises understand their data. You will tackle full-stack engineering challenges end-to-end: from designing scalable microservices in Java (Spring Boot) to building rich, interactive UI components in Angular and TypeScript . You’ll work closely with product and design to turn abstract data modeling into fast, reliable and joyful user experiences. Your work at Celonis will directly impact companies and people around the globe as they improve their processes to save money, reduce waste, improve automation and generally become more efficien

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,