Platform Engineer Jobs

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores You have contributed to in

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores. You have contribute

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based out of our Dublin or Cork office or remotely in Ireland. What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. This is an opportunity to join a team that is responsible for all Observability systems that support metrics, metric visualization, logs, traces, and alerts for MongoDB. We are looking for engineers with high standards, and experience in setting direction and technical leadership for large engineering teams in designing and operating complex distributed systems, with strict SLO on security, durability, availability and performance. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Splunk, Flink, WarpStream/Kafka, Java, Golang Fluentbit. In addition to owning critical components of our observability infrastructure, as a Staff engineer on the team, you’ll also work closely with other SWE, Product and SRE teams to promote and implement best practices in instrumenting and monitoring their services. This is a highly collaborative role, and you will get to own some of the most relied upon internal infrastructure at Mongo. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies low-level systems expertise to build the foundational infrastructure of a popular database, join us! Let’s build a faster, more reliable, and exceptionally observable database system together. W

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maint

As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based remotely on the East Coast What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret metrics, logs, or other data s

Atlas Growth is a cloud engineering group whose mission is to guide customers through their app development journey—from cluster configuration, data modeling and load testing, to running a production workload at scale. We use an in-house experiments platform which helps us validate our features quickly, releasing only the work that positively impacts our customers. Our engineers participate in cross-functional “squads” with product, design, analytics, and research focusing on a single metric (e.g. retention). Our engineering team is part of a larger Atlas Core Engineering org, building foundational elements of MongoDB’s developer data platform. Atlas Growth 2 builds customer-facing features in Atlas and sits alongside other Growth engineering teams. Recent projects include an AI Chatbot for cluster creation, a recommendation system that offers tips for better database performance, and a pricing page designed to optimize conversion rates. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Role Overview Atlas Growth seeks a mid-level software engineer (Software Engineer 3). SE3s are solid contributors to projects they work on and often lead projects of their own. They act in accordance with MongoDB’s core values and leadership principles, and are actively working toward a Senior role. Candidate Profile 3+ years of software engineering experience, with fluency in TypeScript/JavaScript, and experience with a modern framework (e.g. React) Proficiency in Java, Go, C++/C, or a similar compiled language is a plus Experience writing database queries, either document-based or relational Experience writing and reviewing technical specs, and leading small projects Interest in A/B testing or product design Expectations Contribute readable and well-tested code to ongoing projects Collaborate closely with product and design partners to implement and iterate on new customer facing features Write scope and technical spec docs for new projects

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. We are looking for a Senior Automation Engineer to design and scale intelligent automation across Okta’s Enterprise Technology ecosystem. This role will reduce manual operational work, improve developer productivity, and accelerate the software delivery lifecycle across platforms such as Salesforce, NetSuite, AEM, Boomi, identity systems, CI/CD platforms, and other enterprise applications. The engineer will build reliable automation services, reusable integration patterns, and AI-assisted developer agents that understand source code, metadata, configuration, tickets, documentation, deployment history, and operational context. These solutions will automate release activities, identify deployment risks, reduce merge-conflict resolution effort, improve environment management, and enable safe self-service operations. The role requires a combination of software engineering, enterprise application expertise, API and integration development, CI/CD automation, security engineering, and practical experience applying AI to developer and operational workflows. The ideal candidate is comfortable moving between platform-specific technologies and building scalable, secure, platform-agnostic automation frameworks. What you'll be doing Intelligent Automation and Developer Productivity Build AI-assisted developer agents and automation services that reduce repetitive engineering and operational work. Use contextual information from Git repos

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. The Ad Server team is seeking a technical leader to oversee tvScientific’s emerging ad server stack and help drive the ad server independence initiative. This role will be responsible for leading key architectural decisions across core components and integration interfaces, whil