Production Operations Engineer Jobs

Manufacturing Test Engineering Manager Position Summary We are seeking an experienced Manufacturing Test Engineering Manager to lead the development and execution of the end-to-end manufacturing test strategy for next-generation AI server platforms and datacenter infrastructure. This role is responsible for defining and driving the manufacturing test architecture from L6 board assembly through L11 rack-level integration and final system validation , ensuring world-class product quality, manufacturability, and production scalability. This leader will manage a team of 3–5 Manufacturing Test Engineers while partnering closely with Hardware, Firmware, Platform, Validation, Quality, Operations, and Joint Design Manufacturing (JDM) partners. The role owns the manufacturing test strategy, test coverage, factory test infrastructure, manufacturing capacity planning, and continuous improvement of manufacturing quality. Key Responsibilities Manufacturing Test Strategy Define and own the end-to-end manufacturing test strategy from L6 board assembly through L11 rack integration . Develop standardized manufacturing test methodologies that optimize quality, throughput, cost of test, and scalability across multiple products and JDM sites. Establish manufacturing test standards, best practices, and engineering processes that support high-volume server manufacturing. Technical Leadership & People Management Lead, mentor, and develop a team of 3–5 Manufacturing Test Engineers supporting multiple hardware programs. Establish team priorities, allocate resources, and ensure successful execution of manufacturing test deliverables. Foster a culture of technical excellence, accountability, collaboration, and continuous improvement. Serve as the primary technical escalation point for manufacturing test and production issues. Cross-Functional Engineering Collaboration Partner with Hardware, Platform, Firmware, Validation, Reliability, Quality, and Operations teams to ensure manufac

We’re looking for a Software Engineer 3 to join our Marketing Technology Engineering team within Marketing Operations - Technology & Automation. This is a hands-on engineering role for someone who enjoys building reliable, scalable digital platforms and internal systems that improve how teams ship, measure, and optimize web experiences. You’ll work across application development, integrations, experimentation, data-informed decision making, and AI-enabled workflows that help the team move faster and deliver better outcomes. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll do Build and maintain production-quality software that powers martech experiences Design and implement backend services, internal tools, automations, and integrations across the martech ecosystem Improve system reliability, observability, maintainability, and developer experience across the team’s platforms Contribute to experimentation, personalization, and data workflows that support better customer and developer experiences Help evaluate and apply AI-enabled capabilities and tools where they can improve engineering velocity, quality, or user experience Participate in code reviews, technical design discussions, and team planning Take ownership of projects from implementation through rollout, monitoring, and iteration What we’re looking for 3+ years of professional software engineering experience building and supporting production systems Strong coding skills in one or more modern programming languages such as JavaScript or Python Experience building web applications, backend services, APIs, data pipelines, or internal platforms Solid understanding of software engineering fundamentals including testing, debugging, code quality, and maintainability Experience working with cloud services, CI/CD workflows, and modern development practices Ability to work across systems and collaborate effectively with cross-functional partners Strong writte

The Quality Engineer will interact with Corporate Quality, Field Quality, Manufacturing, Design Engineering, and fleet operations to ensure the products released to service are meeting design specifications, functionality, customer expectations, and required documentation. The successful candidate must have the ability to meet tight deadlines, have strong interpersonal and communication skills, be detail-oriented, and be able to work independently. In this role, you will: Manage quality issue tracking to implement Containment, drive Root Cause Analysis and Corrective Action for non-conformances identified during production quality audits and vehicle release process. Support diagnosis of issues reported during Rider Quality Audit and EFR process ; establish standard inspection process and define required tools. Design, champion, and execute strategic continuous improvement initiatives to enhance the effectiveness and efficiency of production quality audit, EFR and issue resolution Work cross-functionally with Supplier Quality, Manufacturing and Vehicle Development to strategically resolve systemic product and process issues. Support develop and review of PFMEA and Control Plans to ensure compliance and robust risk mitigation strategies for all critical manufacturing processes. Good ability to communicate technical results clearly and accurately and drive issues to successful closure. Qualifications BS in Mechanical, Manufacturing, or Industrial Engineering Minimum 8 years of experience in a manufacturing environment, preferably automotive, aviation or contract manufacturing. Proven expertise in advanced problem-solving methodologies (e.g., Shainin Red X, Six Sigma Black/Green Belt) and demonstrated success driving systemic quality improvements across the value stream. Strong planning, organizational, analytical, negotiation, interpersonal, decision-making, oral

P-1578 About Us: The Web Engineering team at Databricks builds and owns the public-facing web experiences that represent Databricks to the world, across databricks.com, the blog, landing pages, hubs, microsites, and event properties. We are rebuilding the platform from the ground up, AI native from the start, and pioneering an agentic SDLC as our operating model. The Role: As Staff Software Engineer, Marketing Agents on the Web Engineering team, you will own the architecture and delivery of agents that transform how Databricks creates, publishes, and ships for the web, shifting content operations from a linear, engineering-dependent process to an orchestrated, continuously improving system. You will define how LLM-powered agents participate reliably across marketing content workflows, set the engineering standards the team builds on, and ensure agent output is robust, observable, and production-ready at scale. The impact you’ll have : Own the architecture and delivery of agentic workflows that enable marketing to self-serve content creation and publishing across blogs, landing pages, microsites, and social, working directly with marketing stakeholders to understand their workflows, define quality criteria, and build tools they trust and use Partner with the Web Platform Staff Engineer on CMS architecture to ensure the content model supports agent read and write workflows and that agent-generated content is structured for AI-driven discovery at production scale Build and own the agent reliability system for this domain: define output quality criteria per workflow, implement eval suites and behavioral regression testing, and build feedback loops that improve agent output over time based on what marketers approve, edit, and reject Architect human in the loop review as a system property across the full publishing pipeline: proposal and commit separation, diff-based review UI, approval routing, notification system, and audit logging that govern when age

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

About the Role: We are looking for a Staff Engineer to steer the technical evolution of our AI-centric business platforms, which currently prioritize ad revenue operations such as cross-system intelligence, workflow automation, and document understanding. While the domain already supports live production traffic and active users, significant architectural challenges remain: how can non-deterministic AI be effectively integrated into workflows where business outcomes depend on high accuracy? Furthermore, how should system boundaries be structured during this phase of rapid platform integration and development? In this role, you will confront this ambiguity head-on—defining architectural patterns, implementing them in production, and validating their effectiveness. About the Team: Tubi’s Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Define and drive the technical architecture of the AI platform — spanning extraction pipelines, confidence scoring, cross-system data aggregation, and user-facing intelligence layers. Ensure systems are modular, testable, and evolvable. Own the platform's most complex subsystems and hardest design problems: reliability under non-determinism, integration across heterogeneous data sources, and progressive automation with appropriate human-in-loop gates. Establish clear system boundaries and integration contracts with adjacent platforms. Design interfaces that are resilient to schema evolution and organizational change. Ship consistently. Turn ambiguous requirements into working software that users see and trust. Bias toward iteratio

About the Team API Multicloud partners with cloud service providers (CSPs) to bring OpenAI’s frontier models and APIs into the cloud environments where developers and enterprises already build. We own the API end to end across CSP platforms, from API integration and request routing through inference execution, capacity management, and day-to-day operations. Our mission is to make these capabilities available broadly and safely while preserving the reliability and developer experience customers expect from OpenAI. Delivering that experience requires work across the stack: adapting API services and cloud-native integrations, bringing up model-serving environments, validating new releases, and operating the systems that connect customer requests to available capacity. We work directly with CSP engineering teams and partner closely with OpenAI’s inference, API, infrastructure, security, and Safety Systems teams. Together, we turn new model capabilities and partner requirements into dependable production services, with attention to performance, operational readiness, and efficient use of compute. Our work contributes to OpenAI’s AWS partnership , including the launch of Daybreak Red and Daybreak Blue on Amazon Bedrock . We’re building on that foundation to bring OpenAI’s API to additional CSPs. These efforts let customers use OpenAI capabilities within the cloud infrastructure, security controls, and workflows they already rely on. About the Role We’re looking for experienced infrastructure engineers to design, build, and operate the systems that run OpenAI’s API across CSP platforms. You’ll help establish the cloud deployment platform: configuring and launching model-serving environments, planning capacity, improving caching and utilization, and making new releases safe and repeatable. Working closely with inference engineers, you’ll connect advances in model serving to the infrastructure and operational practices needed to run them reliably in production. The role call

The Senior Site Reliability Engineer (SRE) is responsible for ensuring the reliability, availability, performance, and operability of production systems across our platforms, by applying software engineering practices to operations, with a focus on automation, observability, and incident response. Responsibilities: Own and improve the reliability, availability, and performance of production services in Google Cloud (GCP). Participate in incident management, including detection, triage, mitigation, escalation, and recovery. Use and improve incident workflows and tooling (e.g., ServiceNow) to ensure clear ownership and timely communication. Design, implement, and operate observability solutions including monitoring, logging, tracing, synthetics, and dashboards (e.g., Splunk Observability, OpenTelemetry ). Reduce operational toil through automation and engineering-led solutions, proactively introducing and driving SRE best practices. Support on-call rotations across multiple time zones, contributing to a sustainable 24/7 support model. Define, monitor, and report SLIs, SLOs, and error budgets for critical services. Drive and be accountable for best-in-class service availability through SRE principles, automation, and proactive reliability engineering. Essential skills and/or Certifications: Bachelor’s degree in Computer Science, Information Technology or related field Strong experience with cloud-native concepts and technologies, with a strong preference for Google Cloud Platform (GCP) and Kubernetes (GKE ). Proven experience with Site Reliability Engineering and production incident management , ideally using platforms such as ServiceNow. Experience with monitoring and observability tools, including metrics, logs, traces, and synthetics (e.g., Splunk Observability, OpenTelemetr

Our Security team keeps Asana's employees, users, and customers safe, by proactively addressing threats and fostering a culture of security throughout our product and operations. We are looking for a savvy Security Engineer to join our Blue Team. You will be a foundational member of the security presence in our Warsaw innovation hub, partnering directly with IT, infrastructure, and product teams to ensure we have robust detection and response capabilities. Detection and response here leans on engineering practice. We are investing in automation and detection-as-code to cut down on manual triage, and we are looking for someone comfortable writing and reviewing code as part of that work. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you'll achieve: Lead detection, analysis, and response across our cloud and SaaS environments, identity providers, endpoints, and the software supply chain , ensuring timely and effective remediation of security incidents. Investigate and remediate security incidents across cloud infrastructure (AWS/GCP/Azure), identity providers (e.g., Okta), and SaaS environments. Investigate and contain software supply chain and CI/CD incidents , from unauthorized changes in build environments to suspect third-party dependencies (e.g., npm, PyPI). Help build and maintain our detection-as-code infrastructure (e.g., Panther), SOAR automation, and response playbooks, treating detection logic as tested, version-controlled production code. Utilize and optimize security tools such as Panther for SIEM, CrowdStrike for endpoint detection and response, and other security platforms. Cond

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We are a software engineering team with expertise in enabling ML models in production. We deploy AI models to run in variety of environments: air-gapped government networks, forward-deployed defense environments, edge nodes, and enterprises with strict data sovereignty requirements. Our customers rely on us for frontier AI capabilities running on hardware they control, often with constrained GPU resources and limited direct access. Rising to that challenge and meeting those expectations is what Palantir's excels at. We treat models like any other software: continuously tested, continually delivered, packaged for reproducible deployment, and built for long-term maintainability. You will own services end-to-end, and work across the full stack, from inference engines, GPU scheduling to deployment pipelines, observability, and integration with Palantir's platform. The goal is to deliver new models and capabilities quickly and continuously. Join us if you want to solve problems at the intersection of infrastructure and machine learning that directly enable critical customers. Technologies We Use Different backend languages, including Java, Rust, Python and Go Model serving engines for GPU-accelerated inference Docker and Kubernetes for containerization and orchestration Industry-standard build tooling, including Gradle and GitHub Core Responsibilities Building high-performance model serving infrastructure that integrates with security models, hardware constraints, and different inference engines Designing intelligent request handling including authentication, rate limiting, concurrency con

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We are a software engineering team with expertise in enabling ML models in production. We deploy AI models to run in variety of environments: air-gapped government networks, forward-deployed defense environments, edge nodes, and enterprises with strict data sovereignty requirements. Our customers rely on us for frontier AI capabilities running on hardware they control, often with constrained GPU resources and limited direct access. Rising to that challenge and meeting those expectations is what Palantir's excels at. We treat models like any other software: continuously tested, continually delivered, packaged for reproducible deployment, and built for long-term maintainability. You will own services end-to-end, and work across the full stack, from inference engines, GPU scheduling to deployment pipelines, observability, and integration with Palantir's platform. The goal is to deliver new models and capabilities quickly and continuously. Join us if you want to solve problems at the intersection of infrastructure and machine learning that directly enable critical customers. Technologies We Use Different backend languages, including Java, Rust, Python and Go Model serving engines for GPU-accelerated inference Docker and Kubernetes for containerization and orchestration Industry-standard build tooling, including Gradle and GitHub Core Responsibilities Building high-performance model serving infrastructure that integrates with security models, hardware constraints, and different inference engines Designing intelligent request handling including authentication, rate limiting, concurrency con

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We are a software engineering team with expertise in enabling ML models in production. We deploy AI models to run in variety of environments: air-gapped government networks, forward-deployed defense environments, edge nodes, and enterprises with strict data sovereignty requirements. Our customers rely on us for frontier AI capabilities running on hardware they control, often with constrained GPU resources and limited direct access. Rising to that challenge and meeting those expectations is what Palantir's excels at. We treat models like any other software: continuously tested, continually delivered, packaged for reproducible deployment, and built for long-term maintainability. You will own services end-to-end, and work across the full stack, from inference engines, GPU scheduling to deployment pipelines, observability, and integration with Palantir's platform. The goal is to deliver new models and capabilities quickly and continuously. Join us if you want to solve problems at the intersection of infrastructure and machine learning that directly enable critical customers. Technologies We Use Different backend languages, including Java, Rust, Python and Go Model serving engines for GPU-accelerated inference Docker and Kubernetes for containerization and orchestration Industry-standard build tooling, including Gradle and GitHub Core Responsibilities Building high-performance model serving infrastructure that integrates with security models, hardware constraints, and different inference engines Designing intelligent request handling including authentication, rate limiting, concurrency con

Our Security team keeps Asana's employees, users, and customers safe, by proactively addressing threats and fostering a culture of security throughout our product and operations. We are looking for a savvy Security Engineer to join our Blue Team in Warsaw. You will be a foundational member of the security presence in our Warsaw innovation hub, partnering directly with IT, infrastructure, and product teams to ensure we have robust detection and response capabilities. Detection and response here leans on engineering practice. We are investing in automation and detection-as-code to cut down on manual triage, and we are looking for someone comfortable writing and reviewing code as part of that work. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve: Lead detection, analysis, and response across our cloud and SaaS environments, identity providers, endpoints, and the software supply chain , ensuring timely and effective remediation of security incidents. Investigate and remediate security incidents across cloud infrastructure (AWS/GCP/Azure), identity providers (e.g., Okta), and SaaS environments. Investigate and contain software supply chain and CI/CD incidents , from unauthorized changes in build environments to suspect third-party dependencies (e.g., npm, PyPI). Help build and maintain our detection-as-code infrastructure (e.g., Panther), SOAR automation, and response playbooks, treating detection logic as tested, version-controlled production code. Utilize and optimize security tools such as Panther for SIEM, CrowdStrike for endpoint detection and response, and other security platforms.