Production Operations Engineer Jobs

About Ema Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. About the role As Ema scales, our corporate IT environment tools, access, devices, and compliance has outgrown an ownership-by-default model. We're hiring an IT Engineer to own it end to end. This is not a traditional helpdesk role. Ema is an agentic AI company, and we expect our own internal operations to reflect that. You'll run corporate IT while systematically automating it, using agentic tooling to remove the manual work rather than absorbing it. The measure of success in this role is how little of it remains manual after a year and every employee’s experience is great. What you'll do Agentic Workflows & Automation: Treat every recurring manual task as an automation candidate, extending existing systems and leveraging AI coding tools to design autonomous workflows. Automated Identity & Access: Shift JML lifecycles, including global employee onboarding, Okta/SCIM provisioning, and access reviews from ticket-driven processes to policy-driven automation. SaaS Lifecycle Automation: Programmatically maintain tool inventories, track utilization, and reclaim unused licenses automatically. Automated Endpoint Security: Manage fleet MDM while automating

Site Reliability Engineer, #1130 Application Monitoring • Production Support • Incident Management • Splunk • AppDynamics • ITIL • Root Cause Analysis • System Reliability • CBP/DHS Location: Ashburn, VA | Onsite, 5 days per week Shifts: 3:00 PM - 11:00 PM Sun thru Thurs 3:00 PM - 11:00 PM Tues thru Sat 11:00 PM - 7:00 AM Sun thru Thurs 11:00 PM - 7:00 AM Tues thru Sat Flexibility to support alternate shifts when coverage is needed is required. Clearance: U.S. Citizenship is required. Must possess a current CBP Public Trust, DHS clearance, or active Top Secret clearance with a background investigation completed within the past three years. Dev Technology Group is looking for a Site Reliability Engineer to join our mission-focused team supporting critical applications for U.S. Customs and Border Protection (CBP). In this role, you'll help keep essential systems running smoothly through proactive monitoring, incident response, troubleshooting, and coordination with technical support teams. You'll be part of a collaborative team responsible for monitoring applications around the clock, identifying potential disruptions before they become larger issues, and helping maintain the reliability of systems that support important government operations. We're looking for someone who enjoys solving problems, can manage multiple priorities, and remains focused when responding to time-sensitive technical issues. What You'll Be Doing: Monitor mission-critical applications and systems to identify performance issues, service disruptions, and potential outages before they impact operations. Respond to system alerts, troubleshoot incidents, assess severity, and coordinate timely resolution with application, infrastructure, and network support teams. Support the Passenger Services Program Directorate's (PSPD) suite of customer-facing applications, helping maintain system availability and performance. Track, document, and update incidents, including business impact, root cause, co

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 Carry out daily production control activities including wafer lot starts, lot monitoring, FOUP management, offload operations, and WIP management in alignment with Fab priorities and output commitments. Use data analytics and AI-enabled tools to monitor production flow, identify bottlenecks, prioritize actions, and support timely decision making on material movement Support offload send/receive operations, ensuring accurate documentation, system transactions, and compliance with established manufacturing procedures. Monitor production performance indicators including WIP levels, aging risks, cycle time impacts, carrier utilization, and capacity constraints; proactively identify abnormalities and bring up potential risks to Production Control Engineers and Manufacturing teams. Leverage AI-assisted insights and digital dashboards to analyze production trends, detect operational exceptions, and recommend actions to improve workflow efficiency and manufacturing performance

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. PagerDuty is looking for a Machine Learning Engineer who is passionate about collaborating with data scientists, product managers and engineers alike. As part of our team, you will help us accelerate the development and extension of products powered by Gen AI and many other shapes of Machine Learning. You’ll be contributing hands-on to the development of the services and pipelines that enable multiple ML/AI features in our product. You will have the opportunity to collaborate with multiple organizations, taking input and guidance from your senior stakeholders and helping bring our initiatives to reality. You’ll succeed by showcasing excellent capacity to manage time, demonstrating emotional intelligence as you navigate stakeholder relationships, and by continuously improving your technical skill set. Key Responsibilities Build and improve the capabilities that enable and accelerate the production of machine learning (ML) and generative AI (genAI) based solutions Partner with data scientists, effectively sharing engineering context and collaborating to support larger initiatives Incorporate the best ava

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. PagerDuty is looking for a Machine Learning Engineer who is passionate about collaborating with data scientists, product managers and engineers alike. As part of our team, you will help us accelerate the development and extension of products powered by Gen AI and many other shapes of Machine Learning. You’ll be contributing hands-on to the development of the services and pipelines that enable multiple ML/AI features in our product. You will have the opportunity to collaborate with multiple organizations, taking input and guidance from your senior stakeholders and helping bring our initiatives to reality. You’ll succeed by showcasing excellent capacity to manage time, demonstrating emotional intelligence as you navigate stakeholder relationships, and by continuously improving your technical skill set. Key Responsibilities Build and improve the capabilities that enable and accelerate the production of machine learning (ML) and generative AI (genAI) based solutions Partner with data scientists, effectively sharing engineering context and collaborating to support larger initiatives Incorporate the best ava

PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for an early-career AI/ML Engineer who is excited to grow at the intersection of two disciplines: large-scale distributed systems and machine learning. In this role you will help build and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll work alongside senior engineers on real production problems, learning how AI features go from a prototype to something that serves reliably at scale. We are looking for a candidate who is genuinely excited about building with modern AI — LLMs, agents, and retrieval — eager to learn how resilient, high-throughput systems are built, and motivated to grow into an engineer who is strong in both. What you’ll do Contribute to AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time data, with support and guidance from senior engineers. Help build and maintain the systems behind them — prompt and agent orchestration, retrieval pipelines, tool/API integratio

About Zencoder At Zencoder.ai , we build and orchestrate AI agents that ship real work - code, research, operations, and more. What started as developer tooling is becoming a platform where people and agents collaborate across knowledge work tasks. The Opportunity We’re looking for a passionate Senior Software Engineer to collaborate on building the next-generation AI coding platform. This is a rare opportunity to join an early-stage company founded by Andrew Filev (founder of a unicorn startup) — to help scale it into a thriving, world-changing business. Together, we’re shaping the future of software development — closing the gap between idea and reality, and influencing not only how code is written, but how progress happens across every field that depends on software. Key Responsibilities You’ll take ownership of designing and building key features. Our stack currently consists of TypeScript and Kotlin and you may be expected to work across all of them. This is not a “just code what’s assigned” role — we’re looking for people with a product mindset, who think deeply about users, bring ideas for product growth, and aren’t afraid to propose and launch new things. We value people who make things happen through their own enthusiasm, rather than waiting for managers to tell them what to do. Here, individual contributors hold the highest status — they are the driving force behind the company’s progress. You’ll work alongside top professionals in an environment that celebrates curiosity, creativity, and results. Essential Qualifications 10+ years of experience building complex, production-grade applications, including deep expertise in backend development in Java / Kotlin / TypeScript. Strong computer science foundation combined with a deep understanding of modern software architecture and design principles — and a proven record of applying them effectively in real-world, user-facing products. Product mindset — you think beyond code, care about the “why” behind the

(P-1286) At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. We are seeking experienced Senior Software Engineers with large-scale distributed system experience to join the Networking Infrastructure team. You will design and automate the networking foundations for large-scale compute clusters across all the major cloud providers, connecting millions of VMs running on Databricks. You will lead the design and development of secure and scalable connectivity that powers all the data / AI workloads. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multicloud and distributed systems challenges. What we look for: 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language 4+ years of experience developing large-scale distributed systems from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. Extensive experience working on large-scale compute clusters, network connectivity, and automation. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is

(P-1286) At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. We are seeking experienced Senior Software Engineers with large-scale distributed system experience to join the Networking Infrastructure team. You will design and automate the networking foundations for large-scale compute clusters across all the major cloud providers, connecting millions of VMs running on Databricks. You will lead the design and development of secure and scalable connectivity that powers all the data / AI workloads. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multicloud and distributed systems challenges. What we look for: 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language 4+ years of experience developing large-scale distributed systems from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. Extensive experience working on large-scale compute clusters, network connectivity, and automation. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is

P-1347 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. And we're setting up the team from scratch in Bengaluru , India. We are seeking an experienced Staff Software Engineers with a networking background to join the Networking Infrastructure team. As one of the seed members of the Bangalore site, you will be focussing on building new backend connectivity services that powers millions of VMs running on Databricks. You will also be leading the design and development of new services that powers the connectivity between our control plane and compute plane. This new platform enables Databricks to increase scalability of our compute plane while also efficiently use cloud resources. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multi-cloud and distributed systems challenges. What we look for: 12+ years of production level experience in one of: Python, Java, Scala, C++, or similar language 7+ years of experience developing large-scale distributed system s from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. Extensive experience working in the Networking dom

P-1347 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. And we're setting up the team from scratch in Bengaluru , India. We are seeking an experienced Senior Software Engineers with a networking background to join the Networking Infrastructure team. As one of the seed members of the Bangalore site, you will be focussing on building new backend connectivity services that powers millions of VMs running on Databricks. You will also be leading the design and development of new services that powers the connectivity between our control plane and compute plane. This new platform enables Databricks to increase scalability of our compute plane while also efficiently use cloud resources. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multi-cloud and distributed systems challenges. What we look for: 8+ years of production level experience in one of: Python, Java, Scala, C++, or similar language 4+ years of experience developing large-scale distributed system s from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. Extensive experience working in the Networking dom

P-926 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. And we're setting up the team from scratch in Bengaluru , India. We are seeking an experienced Senior Software Engineers with a networking background to join the Networking Infrastructure team. As one of the seed members of the Bangalore site, you will be focussing on building new backend connectivity services that powers millions of VMs running on Databricks. You will also be leading the design and development of new services that powers the connectivity between our control plane and compute plane. This new platform enables Databricks to increase scalability of our compute plane while also efficiently use cloud resources. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multi-cloud and distributed systems challenges. What we look for: 6+ years of production level experience in one of: Python, Java, Scala, C++, or similar language 3+ years of experience developing large-scale distributed system s from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. About Databricks Databricks is the Data and AI comp

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI We are hiring Applied AI Engineers to build custom end-to-end AI applications for our public sector clients using the latest developments in the field of AI. You will also get the opportunity to develop and be part of creating custom datasets, evaluations, and fine-tuning these sophisticated models to maximize performance and apply on real world use cases with global reach. At Scale, we’re not just building AI solutions—we are building repeatable blocks to enable the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a member of our rapidly expanding team, we’d love to hear from you. You will: Partner with public sector clients to deeply understand their challenges and define AI-driven solutions Build and deploy end-to-end AI applications into production leveraging latest developments from the biggest AI labs, and open source models Collaborate with cross-functional teams, including data annotation specialists, to create high-quality training datasets Design and maintain robust evaluation frameworks to ensure the reliability and effectiveness of AI models Participate in customer engagements, including occasional travel (approximately two weeks per quarter) Contribute to the scaling of AI capabilities in the public sector through hands-on knowledge sharing Ideally you’d have: A strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience) 7+ years of post-graduation engineering experienc

NVIDIA's Digital Marketing Operations team is seeking a Senior Data Engineer to help build the shared data infrastructure that powers customer engagement, campaign intelligence, and marketing analytics at scale. Our data platform transforms customer behavioral signals, audience definitions, consent records, campaign metadata, and activation outputs into trusted, governed data products for marketing, analytics, personalization, campaign operations, and regional teams worldwide. These products enable audience segmentation, campaign performance measurement, privacy-compliant data activation, identity resolution, and the continued growth of NVIDIA's marketing technology ecosystem. We would love for you to apply today! What You'll Be Doing: Own a key data domain within Digital Marketing Operations, spanning pipelines, data products, audience services, and consumer teams. Shape its architecture and interfaces while anticipating needs related to scale, reliability, performance, privacy compliance, security, cost, and compatibility. Lead complex, cross-functional initiatives. Collaborate across engineering, marketing, and operations stakeholders to translate requirements into clear data architectures, write high-quality code in the critical path, and drive integrations safely into production. Architect, implement, and evolve batch and streaming pipelines that ingest, transform, reconcile, and serve customer behavioral, audience, campaign, consent, and activation data at scale. Build reliable, maintainable systems leveraging distributed processing frameworks, workflow orchestration tools, cloud data warehouses, object storage, and pub/sub messaging platforms. Build and evolve shared data quality frameworks and engineering standards that improve pipeline reliability, consistency, and efficiency across teams. Lead production incident investigations across pipelines, distributed processing, storage, an

Work Flexibility: Hybrid or Onsite **This is a 12 month maternity leave cover** Hybrid, Cork. Position Requirements Will reside within the NPI QE team as part of GQO Quality Assurance organization and work collaboratively with Advanced Operations and Design Assurance, with responsibility for quality assurance activities, including, but not limited to the following: General · Foster collaborative internal/external professional relationships across Design Divisions, Advanced Operations & GQO functions associated with design transfer activities. · Communicate effectively with all internal customers, stakeholders, and project teams to deliver successful project transfers with the highest levels of quality that meet the NPI project goals. · Mentor other groups and functions on areas of expertise with particular attention to design and process transfer. Risk Management · Proficient in risk management practices and tools, having high expertise in failure modes associated with production and production related processes, (PFMEA). · Support the Risk Management File through risk Management Principles. Responsible for the evaluation of process risks, risk mitigation and ensures appropriate production and process controls are identified, qualified, and implemented throughout the product manufacturing lifecycle (from incoming of materials/components, manufacturing, until product release) through robust pFMEA. · Ensure all Risk Management outputs comply with ISO14971. · Support Design team to complete CQA/CTQ identification and inputs to dFMEA. Inspection · Develop and implement lean inspection strategies and inspection plans through state-of-the-art inspection methods and technologies. Ensure inspection