Engineer Ip Verification Jobs

The Infrastructure Engineering team is responsible for building and maintaining a self-service internal development platform that enables MongoDB engineering teams to reliably deploy and operate their own production services and products. We work with numerous engineering teams across the company to understand their infrastructure requirements and development workflows, develop broadly applicable self-service platform services and tooling, continuously monitor how platform services are being utilized, and look for ways to improve developer productivity through automation and education. We are big open source enthusiasts and use a number of open source tools in our stack (contributing upstream whenever possible). Some of the tools we use regularly include Go, AWS, Kubernetes, Crossplane, Terraform, Helm, Drone, Prometheus, and Grafana. However, technology is nothing without a stellar team of engineers that are focused on doing high quality work and working as a team to solve complex distributed computing and platform engineering problems. This is where you come in! We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Our ideal candidate 2+ years of experience managing and mentoring a team of 3+ engineers Has 5+ years of experience owning the design and implementation of large software/infrastructure projects Has built and operated large-scale distributed systems in cloud providers (AWS strongly preferred) Has a strong backend programming background. Fluency in Go is strongly preferred; deep experience with another compiled or strongly-typed backend language is acceptable Pragmatic, detail-oriented, self-motivated, and understands the benefits of collaboration Strong experience operating production Kubernetes clusters, not just deployed to it Has practical experience defining and operating against SLI/SLOs for services they owned Strong experience with observability tooling: metrics, logging, traces, Prometheus, Grafana, OpenTe

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is seeking an accomplished AI Product Sales Specialist to drive sales execution for our AI/ML workload within the Enterprise market. This is a strategic role that works closely with the broader field organization to ensure the successful customer adoption of Snowflake’s Artificial Intelligence and Machine Learning capabilities. RESPONSIBILITIES Achieve pipeline generation and revenue targets for allocated accounts and/or territory on a quarterly and annual basis by developing a sales strategy in the allocated territory with a target account list Execute tailored sales plays to capture market opportunities in AI/ML, helping customers optimize their use of Snowflake's platform. Work directly with customers to understand their AI/ML needs, communicating insights to inform Snowflake’s product roadmap and ensuring alignment with customer requirements. Become an expert in Snowflake’s Artificial Intelligence and Machine Learning solutions and provide executive-level insights to customers and partners, guiding strategic discussions that emphasize the value of Snowflake’s AI/ML capabilities. Work with our Account Executives, Sales Engineers and Field CTOs to drive customer engagements from discovery and qualification through solution implementation and deployment Track, an

The Manager, Business Intelligence leads a team of product owners and reporting engineers who build and maintain the reporting our corporate business areas and venues run on. You set the standard for how data is modeled, defined, and delivered in Amazon Quick Suite (Quick Sight) on top of Redshift and Snowflake, and you connect two halves of the team: the product owners who own the relationship with the business and the backlog, and the engineers who build against it. Success is measured less by dashboards shipped and more by decisions improved — how fast a venue GM or a corporate leader gets a reliable answer, and how much they trust it. Team leadership Lead, coach, and develop a team of BI product owners and reporting engineers; own hiring, onboarding, performance, and career growth across two distinct skill tracks. Develop product owners in requirements gathering, backlog management, stakeholder communication, acceptance criteria, and saying no well. Develop reporting engineers in SQL, data modeling, Quick Suite development, and engineering craft. Hold the line between the two: ensure requirements arrive well-defined and that engineers aren't absorbing unscoped work mid-sprint. Run the team's delivery cadence — intake, prioritization, sprint or release planning, and demo/review — balancing executive asks against roadmap commitments and technical debt. Establish and enforce team standards for SQL, data modeling, version control, code review, testing, documentation, and dashboard design consistency. Product management of the reporting portfolio Own the BI product roadmap across corporate functions and venue operations; make the trade-off calls when demand exceeds capacity. Ensure each business area — Finance, Operations, Marketing, F&B, Guest Experience — has a clear product owner relationship and a visible backlog.<

NVIDIA Architecture Modeling group is looking for Architects, Functional Modeling Engineers, and Simulation experts to join various architecture efforts across GPU/ SOC Architecture teams. A key part of NVIDIA's strength is to innovate in parallel computing fields, delivering the highest performance in the world for high-performance computing. We are constantly looking for ways to improve our SoC and Systems architecture and maintain our leadership. In this position, you will be working with other world-class architects on modeling, analysis and validation of chip & system architectures and features that advance the state of art in performance and efficiency. What you'll be doing: Modeling and analysis of SoC & Systems algorithms and features, across datacenter, automotive, and client products Build and deliver platforms for SOC's that enable left shift for the SW teams aligned with project milestones Work closely with the SOC architects and guide modeling teams to deliver high-quality functional models that involve SOC&#43;GPU use cases Collaborate with our EDA partners to align on customer-facing technologies Develop tests, test plans, and testing infrastructure for new architectures/features and code coverage analysis and reporting Ensure alignment between the various modeling teams at NVIDIA, GPU modeling teams, and modeling teams overseas What we need to see: Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related relevant field (or equivalent experience) with 5&#43; years of relevant work experience. Strong programming ability: C&#43;&#43;, C along with a good understanding of build systems (CMAKE, make) , toolchains (GCC, MSVC) and libraries (STL, BOOST) Computer Architecture background with experience in modelling wit

At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. Feature flags used to be simple on/off switches. That's changing fast. Flags are becoming a control plane: they're tied to observability, they drive rollout decisions, and AI agents build and run more of this work every day. Datadog is building the platform for that future, and we are now expanding our Feature Flagging & Experimentation product to pair flag decisions directly with observability signals and to modernize the flagging workflow for an SDLC increasingly run by agents. As a Senior Product Manager for Feature Flagging, you will own product strategy and drive execution across flags-plus-observability integration and agentic-era flagging workflows. You will set direction for a critical area of the roadmap, work closely with the observability, RUM, and APM teams, and report directly to the Director of Product leading this team. You'll be relied on to make sound, independent product judgment calls with limited oversight, bring engineering credibility to every decision, and drive B2B go-to-market strategy alongside sales. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. This role is based in New York City and works from our office 3 days a week to support that collaboration. What you will Do: Find every place where a flag decision and an observability signal should talk to each other - rollout gating, anomaly-triggered rollback, experiment diagnostics - and ship a roadmap that unlocks observability and experimentation differentiators in Datadog Feature Flags

As an Engineering Manager on Coder’s Core Workspaces team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments. You’ll guide technical direction while growing the team and keeping execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows. What you’ll do here Lead and grow a team within our Workspaces organization. Set technical direction across the agent harness, integrations, and workflows. Stay close to the code and contribute to architecture and implementation decisions. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve reliability, performance, and operability across agentic systems. Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs. What we’re looking for Experience managing and growing software engineering teams. Strong hands-on engineering experience with React and TypeScript . Experience with Go . Hands-on experience building systems around LLMs and agentic workflows. Experience with model APIs, tool calling, context management, or agent loops. Strong distributed systems knowledge. Working knowledge of AWS . Strong technical judgment and comfort working through ambiguity. A track record of helping engineers grow while maintaining a high execution bar. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP , agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute. Experience building abstractions across multiple model providers. Deep experience with AWS, Kube

As an Engineering Manager on Coder’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments. You’ll guide technical direction, grow the team, and keep execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows. What you’ll do here Lead and grow a team within our Agentic Engineering organization. Set technical direction across the agent harness, integrations, and workflows. Stay close to the code and contribute to architecture and implementation decisions. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve reliability, performance, and operability across agentic systems. Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs. What we’re looking for Experience managing and growing software engineering teams. Strong hands-on engineering experience with Go. Experience with React and TypeScript. Hands-on experience building systems around LLMs and agentic workflows. Experience with model APIs, tool calling, context management, or agent loops. Strong distributed systems knowledge. Working knowledge of AWS. Strong technical judgment and comfort working through ambiguity. A track record of helping engineers grow while maintaining a high execution bar. Our tech stack Backend: Go, Postgres Frontend: TypeScript, React Infrastructure: AWS, Kubernetes Observability: Prometheus, Grafana CI/CD: GitHub Actions Bonus tacos if you have (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) Experience building coding agents, developer tools, or cloud development enviro

The Development Infrastructure team builds the infrastructure for the development platform our Asana engineers use every day. We build and operate the software that accelerates how Asana R&D delivers new products to our users. We combine industry best-practices and innovation to enable Asana to remain product-forward delivering a high-quality beloved experience for our users. You will focus on developing the team around you, helping them contribute more and grow as both engineers and individuals. You will channel your passion and enthusiasm as much into recruiting and building a team, as the technical challenges your team will be resolving. This role is based in our Reykjavik 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 Manage and lead a team of 3-7 engineers, including a technical lead, with focus on impactful deliveries Define how the team evolves and interacts with the rest of Asana Recruit for and grow the team Lead the team to identify future opportunities to improve development velocity and the developer experience Influence the future of software development at Asana and guide the technical direction across the organization Collaborate with a world-class team of engineers to enable new development capabilities through infrastructure About you 3+ year of engineering management experience The rare mix of intelligence, empathy, integrity and technical skills that allow you to rapidly earn the trust of a technically astute team Focus on maximizing impact, for yourself and your team Ability to provide valuable input to any technical or product discussion Oriented around the multi-year consequences

As Engineering Manager for Code Security, you'll lead a team of engineers building Infrastructure as Code and Secrets protection - one of the fastest-growing areas inside Datadog's security business, with a strong roadmap and real customer problems to solve. You'll partner closely with Product Management and User Experience to shape how the team delivers, stay hands-on with the technical work, and bring AI deeply into how your engineers build. The organization is still young, which means real room to shape its direction and grow into broader scope as it does. 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 and grow a team of engineers building Datadog's Infrastructure as Code and Secrets security products Own the team's roadmap, staffing, and delivery, partnering closely with Product Management and User Experience Stay hands-on: contribute to code review, weigh in on design decisions, and participate in the on-call rotation Bring AI deeply into how the team builds, from adopting agentic coding tools to rethinking workflows around them Coach engineers at every level, giving direct feedback and helping them grow their scope and careers Keep the team's projects and programs organized as priorities shift across a fast-growing area Who You Are: You've managed software engineers for 2+ years, with a track record of shipping through your team You bring a strong technical background you can draw on in day-to-day roadmap and design conversations You're comfortable staying close to the work - reviewing code and unblocking technical decisions alongside your team You've integrated AI agents into how you and your team deliver code, not just experimented with them You keep projects and programs organized, even as priorities and scope shift &n

Regional Manager, Sales Engineeringとして、Sales Engineersとフロントラインリーダーで構成されるチームを率い、担当地域における技術的な実行力、業務の卓越性、チームメンバーの成長を推進していただきます。 チームパフォーマンスのオーナーシップを持ち、実行基準を形作り、Sales部門のリーダーシップと密接に連携しながら戦略に影響を与え、成果を改善し、個々の案件を超えたインパクトをスケールさせる、いわば「フォースマルチプライヤー(force multiplier)」としての役割を担っていただきます。 Datadogでは、オフィスカルチャーによって築かれる人間関係やコラボレーション、そこからもたらされる創造性を大切にしています。私たちは、従業員それぞれに合ったワーク・ライフ・ハーモニーを実現できるよう、ハイブリッド・ワークプレイスとして運営しています。 業務内容： Sales Engineersのチームを率い、指導・育成し、定期的なフィードバックと構造化された育成プログラムを通じてパフォーマンス、エンゲージメント、長期的なキャリア成長を推進する シニアSalesリーダーシップと自信を持って連携し、地域戦略、複数四半期にわたるプランニング、年間キャパシティプランニング、フォーキャストの整合を担い、2〜3四半期先を見据えてリソースニーズと事業優先度を予測する 戦略的かつインパクトの大きい商談においてエグゼクティブとしての存在感を発揮し、チームとともにシニアレベルのステークホルダーとの連携と技術的信頼性を提供することで、地域レベルの現場での実行をオーナーシップする 評価、顧客エンゲージメント、案件の進行を含む、地域内の技術的セールスサイクル全体を通じて一貫した高品質なデリバリーを監督する IC(個人貢献者)からマネージャーレベルまで、トップタレントの採用・オンボーディングを行い、高パフォーマンスなチームを構築し、構造化されたオンボーディングとイネーブルメントによって立ち上がりを加速させる リソース配分、稼働率、KPIトラッキング、生産性、スキル開発を含む地域内の業務を管理し、担当エリア全体で効果的なカバレッジを確保する Sales、Product、Marketing、Enablement、Supportとシニアレベルで部門横断的に連携し、地域戦略、GTM実行、顧客体験の整合を図る プロセスの改善、データ品質の維持、評価フレームワークのスケール、チームの有効性と事業インパクトを高める施策への貢献を通じて、地域全体の業務の卓越性を推進する 募集要項： 顧客対応型の技術組織においてSales Engineersおよび/またはフロントラインリーダーをマネジメントした経験3年以上。チームパフォーマンスの管理、メンバー育成、高パフォーマンスチームのスケールにおける実績を持つ方 Sales Engineering、Solutions Engineering、または技術系の顧客対応職における経験7年以上 シニアSalesリーダーシップと戦略的パートナーとして、地域戦略、長期プランニング、フォーキャストの整合において連携した実績 複数四半期にわたるプランニングと日々のチーム実行・優先事項のバランスを取りながら、戦略レベルと業務レベルの両方で活動できる能力 部門を横断し、シニアレベルにも影響を与えられる強力なコラボレーション力 パブリッククラウド(AWS、Azure、GCP)、Kubernetes、APM/トレーシング、セキュリティ、開発者体験、オブザーバビリティに関する背景・知見 AIツールを活用し、それをスケールさせる実証済みの能力 変化を受け入れ、好奇心を持つ成長志向のマインドセット 顧客対応をサポートするために必要に応じて出張できること Datadogは、さまざまな立場の人々を大切にしています。誰もが初日から上記の資格をすべて満たすわけではないことは理解しています。それでも構いません。テクノロジーに情熱を持ち、スキルを伸ばしたいと思っている方は、ぜひご応募ください。 福利厚生とキャリア成長： 新入社員への株式付与（RSU / 譲渡制限付株式ユニット）および従業員株式購入制度（ESPP） 継続的な専門能力開発、製品トレーニング、キャリアパスの提供 社内ネットワーク構築のためのメンターおよびバディ・プログラム インクルーシブな企業文化、コミュニティ・ギルドへの参加機会 幅広く手厚い医療関連の福利厚生制度 企業型確定拠出年金（401K） ペットの養子縁組と保険プログラム 上記の内容は、就業する国やDatadogでの雇用内容によって異なる場合があります。 #LI-Hybrid About D

At Datadog, we’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Observability Data Platform (ODP) is the backbone of everything Datadog delivers – powering how data is ingested, stored, routed, and surfaced across every product at planet scale. As a Senior Product Manager for ODP, you will work with world-class engineers and cross-functional partners to shape how the platform is deployed, controlled, and operated. You will define product direction across the control plane and data layer, translate complex infrastructure trade-offs into clear roadmap decisions, and help customers get the most from their observability investment – regardless of architecture, topology, or scale. 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 Will Do: Develop a deep understanding of the Observability Data Platform customers – platform engineers, SREs, and product managers that own the product verticals – their infrastructure challenges, deployment topologies, and cost-to-serve trade-offs. Define product direction across multiple ODP surfaces, including the control plane and data layer, by articulating clear problem statements and desired outcomes, and partnering with engineering on technical approach and sequencing Lead conversations with design partners and strategic customers to understand real-world platform pain points, validate product assumptions, and guide solutions from early prototypes through General Availability Develop a co

Datadog's Technical Solutions (TS) organization is one of the largest organizations in the company — spanning Sales Engineers, Technical Account Managers, Enterprise Customer Success Managers, Technical Support Engineers, and Solutions Architects who work with prospects and customers across every stage of their journey with Datadog. Technical Solutions Operations (TSO) exists to make that organization faster, smarter, and more scalable. We build the systems, analytics & programs that give TS teams more leverage — and we measure our success by the business outcomes we drive, not the projects we complete. The programs this team runs touch every function in TS, and the operating model you build will define how that scales. We're looking for a Director of Technical Program Management to lead the TSO Program Management team. This role sits at the intersection of strategy and execution: you'll own the programs that shape how TS operates at scale, lead a team of technical program managers, and serve as a peer to the Directors and VPs who run the teams you support. Your counterparts are leaders overseeing hundreds of customer-facing technical professionals, and your role is to successfully interface with each organization with proactive solutions on how your team can help them be more effective. This is a rare opportunity to lead a function where the output isn't a deliverable, it's organizational capability. If you want to build something that compounds across an entire organization, this is the role. 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 Run the PMO as a business impact function. Own the PMO operating model end-to-end, including intake, prioritization, scoping, execution, and impact measurement — with every program directly linked to measurable bu

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

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r