Cloud Security Engineer Jobs

Role Summary: Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines with log management software that customers deploy and manage in their own infrastructure. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at 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’ll Do: Make customer-controlled deployments feel like a managed Datadog product: deployment, upgrades, configuration, observability, diagnostics, reliability, and secure operation across diverse customer cloud environments Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably that customers deploy and operate within their own cloud infrastructure. Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have significant experience building software that is installed, deployed, and operated in customer environments rather than only as a fully managed SaaS service. You have strong expertise in distributed systems,

Our Enterprise Sales Executives target and close new business with Datadog’s largest, most strategic customers and prospects. In this role you’ll be focused on uncovering the pain points organizations face as they operate in or migrate to a cloud environment at scale as well as delivering the appropriate Datadog solution. 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: Prospect into large Fortune 1000 companies while running an efficient sales process Maintain, build and own specific relationship maps for your territory including existing relationships and aspirational contacts Develop a deep comprehension of customer's business Negotiate favorable pricing and business terms with large commercial enterprises by selling value and ROI Handle existing customer expectations while expanding reach and depth into assigned territory Demonstrate resourcefulness when faced with challenges that defy easy solution Have intuitive sense of necessary steps to close business and gain customer validation Identify robust set of business drivers behind all opportunities Ensure high forecasting accuracy and consistency Who You Are: Someone with 3+ years closing experience (mix of field selling within mid-market or enterprise) Driven and have met/exceeded direct sales goals of 1M+ and operated with an average deal size of $100k+ Able to demonstrate methodology to prospect and build pipeline on your own Experienced in working for an innovative tech company (SaaS, IT infrastructure or similar preferred) Experienced in selling into large Fortune 1000 companies with the ability to win new logos Role requires regular travel to client sites, within your area and other regions, using various modes of transportation (car, train, air), depending on business needs. Fluent

MongoDB is seeking a Senior Partner Marketing Manager to build and scale high-impact go-to-market programs with strategic cloud, technology, AI, and ecosystem partners. This role will contribute to the partner marketing strategy and execution across integrated campaigns, launches, events, digital programs, co-marketing motions, marketplace activation, and marketing enablement. Working closely with Partner team, Specialists,, Partner Strategic Operations, Alliances, Field Marketing, Global Demand Center, Product Marketing, Sales Enablement, and Communications teams. Reporting to the Lead, Partner Marketing, the successful candidate will help drive customer adoption through partner attach and generate partner-sourced and partner-influenced pipeline, while creating repeatable programs that scale across regions and partner types. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Key Responsibilities Translate partner capabilities, integrations, APIs, and AI solutions into compelling marketing messaging and experiences for developers, architects, IT decision-makers, executives, partner sellers, and marketers Develop customer-outcome-led messaging and campaigns that clearly articulate the better together value of MongoDB plus partner Plan and execute integrated, multi-channel programs leveraging the Global Demand Center and their offerings across direct, organic and paid channels Support cloud marketplace, solution-listing, integration, launch, and post-launch adoption motions where applicable working closely with Cloud Partner Marketing team Create scalable marketing activation assets for partners including campaign-in-a-box kits, co-marketing plays, solution briefs, messaging guides, battlecards, demos, webinars, training, and customer-facing content Build repeatable partner marketing playbooks, content kits, and operating processes that can be localized and scaled across partners and regions Lead partner-facing events,

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Senior Data Engineer will be responsible for delivering high quality modern data solutions through collaboration with our engineering, analysts, data scientist, and product teams in a fast-paced, agile environment leveraging cutting-edge technology to reimagine how Healthcare is provided. You will be instrumental in designing, integrating, and implementing solutions on-premise as well supporting migrations of existing workloads to the cloud. The Senior Data Engineer is expected to have extensive knowledge of modern programming languages, designing and developing data solutions. The position is open in a data engineering team that is responsible for processing payer files into our Data Warehouse. Required Qualifications 6&#43; years of experience working with SQL and relational database management systems 3&#43; years of experience in Cloud Data Engineering Platforms such as AWS, GCP, Azure, Databricks, Snowflake etc. 3&#43; years of experience in on-prem Data Engineering Platforms such as Microsoft SQL Server, Oracle, Teradata etc. Programming and modifying code in languages like SQL, Python, and PySpark to support and implement Cloud based and on-prem data warehousing services.</spa

Job Requisition ID # 26WD101160 Position Overview As an Implementation Consultant focused on our Forma Industry Cloud for Construction General Contractors and Trade Contractors, you will bring industry expertise, strong product knowledge, and engaging communication and presentation skills, to help customers put innovative solutions into practice. In this role, you will work with customers to evaluate current workflows, identify opportunities for transformation, and guide the adoption of digital solutions that support better business and project outcomes. You will partner with customers to define new workflows, configure technology, deliver training, and support lasting adoption. This role is designed for someone who can credibly speak to the full building lifecycle and connect Autodesk Forma Industry Cloud solutions to customer priorities across the plan, design, build, and operate journey. This role will primarily support North American accounts, with a particular focus on strategic General Contractors and Trade Contractors. You will help customers scale impactful solutions across their organizations, while also partnering closely with Autodesk product and sales teams to share feedback from the field and stay aligned with product roadmap direction. You will report to a manager on the Adoption Services team. Responsibilities Lead end-to-end Forma product implementation, training, and consulting engagements focused on Forma Build and Preconstruction Partner with customers to assess workflows across planning, design, construction, and operations, and recommend best practices using Forma Industr

Enterprise Advanced is a distributed team across Europe and India that builds the software running MongoDB on any infrastructure, at global scale — from on-prem data centers to private cloud. You'll work primarily on Ops Manager and Automation, the systems that let customers deploy fault-tolerant, globally distributed MongoDB clusters in minutes. Our software manages some of the largest self-managed MongoDB deployments in the world, with production clusters running hundreds of shards and nodes under a single deployment. The main focus of this team is to adapt our software to manage MongoDB clusters which are deployed in data centers or private cloud platforms. You will work on the core functionality for all of our products, mainly on the Ops Manager , and Automation products. Our team's end users are some of the largest businesses in the world, deploying massive clusters and processing huge amounts of data. This role is based in our Gurgaon office, and can work in a hybrid fashion. This role will report to the Senior Engineering Manager also based in our Gurgaon office. What you’ll do Design, implement, test, and release features for Ops Manager Own end-to-end delivery of complex projects, from design through incremental shipping Troubleshoot and resolve issues surfaced in customer deployments running at scale Apply engineering judgment and MongoDB's core values across planning, design, and code review A great fit for this role will be You enjoy distributed-systems problems; consistency, fault tolerance, and scale are the daily reality, not edge cases People who like ambiguity and are comfortable defining their own approach with guidance, not step-by-step instruction You're flexible! You're willing to take on a wide variety of responsibilities, learning as you go You're a self-starter! You're comfortable organizing your own time, acting on feedback and prioritizing with guidance from senior members of your team Requirements 4+ years experience with a language

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Role Summary At CVS Health®, you’ll be working with a team of passionate colleagues who care deeply, innovate with purpose, hold themselves accountable and prioritize safety and quality in everything we do. Do you enjoy innovation while having fun doing it? If the answer yes, then this role might be for you! Join us and be part of something bigger, innovative and simplification in healthcare. We are seeking a highly experienced and innovative Principal (Director Level) Software Development Engineer to lead the application architecture, design, development, delivery of next-generation digital applications (including Reporting and financial solutions), and optimization of scalable, secure, and high-performance solutions leveraging AI across all major cloud platforms (AWS, Azure, and GCP). This role requires deep technical expertise, AI-enabled solutions, strategic thinking, scalable digital platforms, and enterprise integrations that power critical healthcare and pharmacy experiences and a passion for driving excellence in software engineering practices. This is a senior technical leadership role for a hands-on engineer who can operate across the full stack—from intuitive front-end applications to resilient backend services—while setting architectural direction, influencing engineering standards, and mentoring teams. The ideal candidate combines deep technical expertise, platform thin

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. Responsibilities: Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality Building and maintaining automated pipelines that will enforce the correctness of code examp