Automation Operation System Engineer Jobs

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

We're looking for an individual to own, evolve, and grow the Team TaylorMade Rewards program across our eCommerce business within our largest market. In this role you will be the program's day-to-day champion — owning commercial execution, shaping strategy, driving member engagement and owning optimization of points while partnering cross-functionally to make loyalty a genuine competitive advantage. This is a high-visibility, high-impact role at the intersection of data, marketing, and customer experience. US Commercial Ownership Own the US Team TaylorMade Rewards program, including earning and redemption mechanics, and member lifecycle strategy in TM’s largest market. Develop and maintain the US loyalty financial model ensuring the loyalty investment drives measurable ROI through repeat purchase rate, LTV, and contribution margin. Drive the commercial evolution — identifying new earn/burn opportunities, partnership integrations (e.g., ID.me, subscriptions), and feature enhancements. Identify and develop early access and exclusive product opportunities for loyalty members — defining eligibility criteria, coordinating with merchandising and product teams on inventory allocation, and ensuring these benefits are clearly communicated and differentiated across member tiers. Commercial Management & Execution Design and execute targeted loyalty campaigns (bonus point events, triple-point promotions, milestone rewards) tied to key product launches, seasonal moments, and tour activations. Own loyalty member automations across email, SMS, and push notifications — including trigger logic, segmentation, and messaging strategy — and track performance against key engagement metrics such as open rate, click-through rate, conversion, and churn reduction to continuously optimize the member lifecycle. Collaborate with the US retention team to build pers

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

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview As a Senior Engineer, Marketing, you'll be embedded with the Marketing team, providing us with technical leadership, consulting, and systems thinking. You'll assemble the orchestration systems, integrations, and AI capabilities that help teams work faster, and in more data‑driven ways. You will lead end‑to‑end design, implementation, and management of the marketing campaign lifecycle system, integrations, internal tools, and learning/experimentation infrastructure. You will report to our Director, Advertising Systems. Responsibilities: You will write high-quality, secure, and well-tested code, contributing to standards and documentation for Marketing infrastructure, data models, and tools You will build the campaign lifecycle orchestration backbone You will build integrations and internal tools that connect project management, collaboration, creative, media, and email/lifecycle platforms You will work with Marketing partners as a technical advisor, translating needs into designs You will integrate AI agents and automations (including LLM-powered flows) into Marketing workflows according to company GenAI guidance You will design and operate data pipelines and models that ingest marketing and performance data into a data layer, supporting experimentation and analytics workflows You will deliver abstractions and APIs that ensure AI systems and our users to create campaign wrap-ups, insights, next-t

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: We're looking for a Senior Recruiter to build our go-to-market teams. Vercel is defining what the web looks like in the AI era, and the people you hire will bring it to market. Recruiting is a product here, and building it means automating workflows, rethinking processes, and shipping with the newest AI models and agents, the same ones our engineers use. This is a hybrid role based in New York City or San Francisco, with three days a week in the office. What You Will Do: Run full-cycle searches for all roles you work on, from kickoff with the hiring leader to close. Source candidates: proactively source, manage inbound, utilize your network and referrals to find and close top talent Use AI to ship automations, tools, workflows and resources for yourself and the team Be the expert in the room by utilizing market data, making clear recommendations, and pushing back when there is misalignment Partner directly with our executives and run every search like an executive search. About You: 6+ years of full-cycle recruiting, including go-to-market roles such as sales, field engineering, and/or partnerships Experience hiring sourced candidates from your own direct outreach Proven use of AI tools in recruiting, with measurable speed or quality gains Technical curiosity, a pulse on the market and a bias for action Bonus If You: Build AI tools, agents, or automations that redefined how you operate Recruited for a developer, infrastructure, or frontend company Compensation & Benefits: Competitive compensation package, including equity. Incl

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the Role: As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes. What You'll Do: Customer-facing: 80% working directly with customers. Coding & Integration: 70-80% hands-on technical implementation Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows. Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow. Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the Role: As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes. What You'll Do: Customer-facing: 80% working directly with customers. Coding & Integration: 70-80% hands-on technical implementation Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows. Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow. Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Position Summary The Director of Central NPM & Inventory Control is responsible for leading Micron's global Assembly & Test New Product Management (NPM) execution and inventory governance across the network. This leader drives end-to-end NPI execution excellence, inventory health, build commitment reliability, cycle time optimization, and planning transformation initiatives. The role serves as the critical bridge between Product Development Teams (PDT), Supply Chain Planning (SCP), Site NPM organizations, Manufacturing, and Business Units to ensure successful NPI execution, predictable customer commitments, efficient inventory utilization, and scalable planning processes. The Director will lead a globally distributed team responsible for: Central New Product Management ( NPM) governance Build Plan Commit management Demand line fulfillment Model Cycle Time(CT) governance WIP and execution management Inventory X control NPI to HVM transition readiness Planning process transformation and automation AI/System-enabled plannin

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Validation Execution Lead end‑to‑end Validation Run execution in a high‑pressure, fast‑paced environment , ensuring on‑schedule starts/completions , risk‑aware re‑plans , and efficient IQP/ETV material usage . Own time‑bound data crunching pipelines (automated log parsing, metrics aggregation, anomaly ranking) and deliver decision‑ready summary reports and sightings by agreed Cycle Time . Guarantee coverage completeness across MBIST and Native flows; drive Hot/Cold corners , TSV screen/AQLK , async timing boundary coverage, and evidence‑backed closure . Platform Leadership Develop and debug test programs on SM3/Cobra and Advantest V93K ; enforce code quality, reviews, and release discipline. Align hardware configs ( handler, socket, loadboard, probe card ) to test intent and throughput targets. Advanced Analysis, Verilog Simulation & Automation Perform power/thermal characterization ; correlate IDD/thermal data with performance/reliability; author recommendations for content changes and silicon fixes. Architect and execute

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities Validation Execution Assist in executing Validation Runs on IQP/ETV materials under defined timelines, ensuring coverage completeness across MBIST and Native Mode flows. Support time-bound data crunching (log parsing, statistical summaries) and contribute to summary report preparation. Platform & Test Program Support Operate and debug programs on SM3/Cobra (MBIST) and Advantest V93K (Native) . Assist in hardware readiness: handler, socket, loadboard, and probe card setup. Technical Analysis & Simulation Validate high-speed I/O (>11 Gbps) and assist with eye diagram and signal integrity checks. Support Verilog simulation tasks (testbench execution, waveform review) to reproduce sightings and validate fixes. Data & Automation Develop basic scripts in Python for log parsing and data visualization. Maintain documentation in Confluence/Jira and version control in Git/Perforce. Debug & Collaboration Participate

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Validation Execution Lead end‑to‑end Validation Run execution in a high‑pressure, fast‑paced environment , ensuring on‑schedule starts/completions , risk‑aware re‑plans , and efficient material usage . Own time‑bound data crunching pipelines (automated log parsing, metrics aggregation, anomaly ranking) and deliver decision‑ready summary reports and sightings by agreed Cycle Time. Guarantee coverage completeness across Validation flows; drive Hot/Cold corners , screen , timing boundary coverage, and evidence‑backed closure . Platform Leadership Develop and debug test programs on ATEs like Advantest and In-house ATE; enforce code quality, reviews, and release discipline. Align hardware configs ( handler, socket, loadboard, probe card ) to test intent and throughput targets. Advanced Analysis, Verilog Simulation & Automation Perform power/thermal characterization ; correlate IDD/thermal data with performance/reliability; author recommendations for content changes and silicon fixes. Architect and execute Verilog simulations (bench cre