Engineer Ip Verification Jobs

Datadog's Application Performance Monitoring (APM) provides deep visibility into the health, performance, and lifecycle of modern distributed applications, tracing requests from end-user devices (web and mobile) through to backend services. Our goal is to help customers detect root causes faster, optimize application performance, and improve resource efficiency at scale. As the Engineering Manager for APM Serverless, you will help define and deliver the end-to-end serverless APM experience, from auto-instrumentation through troubleshooting, and ensure that OpenTelemetry and Datadog-native customers alike have a frictionless and performant journey. You will also lead efforts to expand coverage of cloud-managed services across providers, ensuring customers can seamlessly trace and monitor critical services in all major and emerging cloud environments. We’re looking for an experienced engineering leader who thrives at the intersection of infrastructure and developer experience. You should care about well-designed APIs, observability-first thinking, and building systems that empower other developers. This is a high-leverage role that will influence how developers across the industry understand and instrument their serverless workloads. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Lead a polyglot team of 8-9 engineers and partner closely with Product and Engineering teams across Datadog to deliver industry-leading serverless capabilities that power consistent, scalable, and intuitive instrumentation across languages. Drive a domain that is technically rich: Lambda, Azure Functions, GCP, OTel billing, Rust, durable functions, distributed tracing across managed services. Engineers on this team work

Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog. 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 Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets) Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions) Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops Define how observability data and business data come together to serve unique use cases Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs Work on the product pricing Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools Who you are 5+ years of experience

Today, organizations struggle to ensure their most important digital experiences are working as intended because observability data is scattered across products and siloed in logical layers of their technical stack. We're building the system that fixes this: Journey Monitoring, a single centralized hub that brings together Real User Monitoring (RUM), Synthetics, and Product Analytics to bridge the gap between system health and user success. You'd be building a product that establishes a new functional observability layer, enabling teams to auto-discover journeys, track conversions and uptime side-by-side, and trace root causes across their full stack without cross-team handoffs. What you'll do: Drive the product vision and roadmap spanning the Journey Monitoring hub, including the journey map, details reports, automatically inferred journeys, and cross-product data federation. Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers, and other PMs across the Digital Experience Monitoring (DEM) products. Deeply understand the needs of distinct key personas: SREs and engineers (who monitor uptime and troubleshoot technical performance), product managers (who track conversion and investigate behavioral drop-offs), and business leaders (who care about outcomes and revenue impact). Design the functional observability layer that makes end-to-end flow monitoring intuitive — including the auto-discovery of user journeys from real traffic, Experience Level Objectives (XLOs), and seamless Bits AI integrations for automated root-cause investigations. Define how behavioral data and technical data come together to automatically surface whether a drop in conversion is caused by a technical failure (like a breached SLO) or a behavioral friction point. Engage directly with early customers and internal dogfooding users to iterate on usability, refine the journey map, and optimize the cross-sell and up-sell paths for

As the Senior Product Manager for Network Path, you’ll own the vision, roadmap, and execution for how our customers visualize, monitor, and troubleshoot network traffic across complex hybrid and cloud environments. You’ll work closely with a diverse set of Network, DevOps, and SRE teams to understand how they manage their infrastructure, what challenges they face regarding network visibility and routing, and how our product can help them better observe, isolate, and remediate latency, packet loss, and connectivity issues across the public internet, cloud providers, and private data centers. In addition, you’ll work with product teams across the organization to identify opportunities to create integrated experiences—bridging the gap between infrastructure monitoring, application performance, and network health—and you’ll partner with engineers, designers, and go-to-market teams to drive adoption across thousands of customers. 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: Define the strategy and pioneer new ways to visualize end-to-end network paths. You will determine how we capture, analyze, and map complex routing data to give customers a true hop-by-hop view of their network traffic. Own the core Network Path roadmap, ensuring deep coverage for cloud-native networking (e.g., AWS VPCs, Transit Gateways), SD-WAN, and traditional on-premise routing topologies. Explore ways to combine flow and metrics to provide a holistic view of network health and pinpoint the problem. Partner with Product Marketing to articulate the business value of network path monitoring, showing customers how improved visibility directly correlates to reduced MTTR and optimized cloud egress costs. Identify opportunities to build intelligent alerting and root-cause analysis c

MongoDB is seeking an Engineering Manager to join the Atlas Organization. The organization is responsible for building MongoDB Atlas, our database-as-a-service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Cork and would like a hybrid or in-office working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core Values We’re looking for someone who Has at least 6 years of professi

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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: Lead the strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

MongoDB is seeking an Engineering Manager to join the Atlas Organization. The organization is responsible for building MongoDB Atlas, our database-as-a-service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Dublin and would like a hybrid or in-office working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core Values We’re looking for someone who Has at least 6 years of profes

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

Senior Product Manager, Cluster Scalability Location: Dublin About the Role MongoDB is hiring a Senior Product Manager to own scalability for the Atlas data platform. Atlas is how the world’s most demanding applications run on MongoDB — from real-time gaming and financial transactions to AI workloads with unpredictable traffic patterns. When those applications grow, slow down, spike, or contract, scalability is the layer that decides whether the customer trusts us to keep running their business. This role owns the end-to-end product experience for how customers scale up, scale down, and horizontally scale their Atlas deployments. That includes vertical scaling (instance tier changes), autoscaling, horizontal scaling (sharding and shard key strategy), and the operational workflows around all of them. You will set the strategy, drive execution with engineering, and be accountable for measurable year-over-year improvements in how reliably and predictably customers scale. We care less about whether you’ve worked on databases before and more about whether you’re the kind of PM who can ramp fast on a hard technical domain, form a clear opinion about what needs to happen, and defend that opinion to senior engineers, field partners, and enterprise CTOs, especially when they disagree with you. Database and scaling concepts are teachable. Judgment, conviction, and crispness are not. Responsibilities Set a clear, opinionated vision and strategy for Atlas cluster scalability and translate it into concrete, prioritized bets each release. Own the end-to-end roadmap for vertical scaling, autoscaling, and horizontal scaling, including the operational and observability surfaces customers rely on during scaling events. Make hard prioritization calls, including saying no to things with real customer or leadership support, and own those decisions and their consequences. Build deep technical understandin

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field Strong background in machine learning, deep learning, and natural language processing Familiarity with training distributed training of neural networks for language and visual understanding What We Offer Opportunity to work on real-world problems at the cutting edge of AI research Opportunity to utilize research vision to innovate the entire company and make real-world impact Exposure to the full lifecycle of AI model development, from research to production Our compensation (base + equity) for this position is competitive with frontier AI labs About MongoDB

MongoDB Professional Services serves as the delivery owner for complex customer initiatives, translating strategic goals into disciplined execution and measurable business outcomes across modernization, migration, cloud, data, and AI-related programs. The team drives delivery accountability across customers and internal stakeholders through strong governance, proactive risk management, and sustained alignment to customer priorities. About the Role MongoDB is looking for a Senior Project Manager to lead complex customer-facing Professional Services engagements and serve as the accountable delivery owner for customer requirements, execution, and business outcomes. The role translates customer objectives into a clear delivery strategy, aligns execution to expected outcomes, and drives alignment across scope, schedule, risk, dependencies, stakeholder actions, governance, and success measures. The person acts as a consultative partner to the customer’s business. helping shape priorities, tradeoffs, and decisions while keeping delivery focused on value realization. They must bring strong services delivery leadership, executive communication skills, and the ability to operate effectively in technically complex environments with sound judgement. The role partners closely with Consulting Engineers, Customer Success, Sales, and customer stakeholders to maintain momentum, align resources, and deliver measurable value. It also operates at both the engagement and broader account level, including leading regular quarterly business reviews and helping teams reassess priorities when needed. This role will be based remotely in the United States. What you will do: Lead complex Professional Services engagements from kickoff through closeout, maintaining continuity, accountability, and focus on value realization Own delivery accountability for customer requirements, execution, and business outcomes, keeping work aligned to customer prior

We’re looking for a Senior Engineering Manager who is ready to lead through ambiguity and improve how software gets built at MongoDB. This role leads teams focused on developer productivity, with an emphasis on measurable improvements to the software development lifecycle. This role can be based remotely in the United States. The Team The AXIS team (AI, X-functional tools, Insights, and Signals) sits within Developer Productivity and is responsible for overseeing the metrics and observability infrastructure of our expansive developer environment to help build a strong data-driven culture. You’ll also be a key partner in building the agentic ecosystem for AI-driven development across engineering. Candidate Profile We’re looking for an experienced leader with a passion for solving the big challenge of measuring developer productivity and providing the actionable signals that help teams improve their performance. They should be comfortable working collaboratively with other leaders and partners across our Engineering and Data teams in maximizing the use of data for insights and AI enablement. The right candidate for this role will have 4+ years of experience managing software engineers, including hiring, performance management, growth planning, and compensation; required for external candidates and preferred for internal candidates 8+ years of hands-on software engineering experience building and operating production systems; experience in developer tooling, platform engineering, observability, or data engineering is a strong plus Demonstrated the ability to lead through ambiguity, work across team boundaries, and deliver outcomes without close supervision Strong customer orientation and sound judgment in finding practical, high-leverage solutions Experience working with systems involving analytics, data pipelines, and metrics platforms Experience with AI tools development and enablement efforts Strong technical judgment, including the ability to evaluate t

We’re looking for a Senior Engineering Manager who is ready to lead through ambiguity and improve how software gets built at MongoDB. This role leads teams focused on developer productivity, with an emphasis on measurable improvements to the software development lifecycle. This role can be based remotely in Canada. The Team The AXIS team (AI, X-functional tools, Insights, and Signals) sits within Developer Productivity and is responsible for overseeing the metrics and observability infrastructure of our expansive developer environment to help build a strong data-driven culture. You’ll also be a key partner in building the agentic ecosystem for AI-driven development across engineering. Candidate Profile We’re looking for an experienced leader with a passion for solving the big challenge of measuring developer productivity and providing the actionable signals that help teams improve their performance. They should be comfortable working collaboratively with other leaders and partners across our Engineering and Data teams in maximizing the use of data for insights and AI enablement. The right candidate for this role will have 4+ years of experience managing software engineers, including hiring, performance management, growth planning, and compensation; required for external candidates and preferred for internal candidates 8+ years of hands-on software engineering experience building and operating production systems; experience in developer tooling, platform engineering, observability, or data engineering is a strong plus Demonstrated the ability to lead through ambiguity, work across team boundaries, and deliver outcomes without close supervision Strong customer orientation and sound judgment in finding practical, high-leverage solutions Experience working with systems involving analytics, data pipelines, and metrics platforms Experience with AI tools development and enablement efforts Strong technical judgment, including the ability to evaluate tradeoffs, i

MongoDB is seeking an Engineering Manager to join the Atlas Clusters Organization. The organization is responsible for building MongoDB Atlas, our database-as-a-service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. The Atlas Clusters Fleet Signal Management team is a product engineering team that builds machinery to rollout hardware and software to the Atlas data plane, detect regressions at scale, and automate remediative actions. The core mission is to establish platform stability by owning the rollout and monitoring systems designed to swiftly detect and mitigate potential issues. We are forming a new Atlas Clusters Fleet Signal Management team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core V

AI frameworks like LangChain, LlamaIndex, and n8n are quickly becoming the default way developers build with AI — and MongoDB wants to be the data platform that shows up everywhere they build. As part of the AI Builders Experience org at MongoDB, we’re forming a brand new engineering team to make that happen, and we're looking for the founding Engineering Manager to hire the team, set the technical direction, and ship integrations into some of the fastest-moving open-source ecosystems in tech. In this role, you'll be close enough to the code to jump into exploratory work yourself while also building the team, process, and operational rigor to keep a growing integration portfolio healthy long-term. The new team will work mostly in Python and TypeScript while collaborating closely with client library teams and other engineering groups across MongoDB that deliver the underlying driver, platform, and product capabilities needed to support these integrations well. You’ll collaborate closely and move quickly with product, partners, field teams, the developer community, and open source project maintainers to ship where demand is real, deepen investment where adoption proves out, and evolve the portfolio over time as it becomes a critical part of MongoDB’s future in AI. MongoDB engineering teams pride themselves on building high-quality software and living our values every day. We value intellectual curiosity, intellectual honesty, customer empathy, 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 recruiting to hire a team of Python and TypeScript engineers who will build and own MongoDB integrations across a broad AI framework ecosystem that includes technologies like Langchain, LangGraph, LlamaIndex, n8n, and Mastra Execute effectively in a fast-moving environment where priorities may shif