Security Technical Program Manager Salary India Jobs

We are building the best platform in the world for engineers to understand, scale, and protect their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, application tracing, and security insights for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way . 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: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all

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. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. 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 APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially agentic on

Developers are shipping more code than ever, accelerated by AI-assisted development and increasingly complex software delivery workflows. As a Product Manager II on the Developer Engagement team, you'll help bring Datadog's insights and automation directly into the tools developers use every day, making software delivery faster, safer, and more efficient. You'll define customer-facing experiences that connect Datadog's observability, CI/CD, testing, security, and AI capabilities with pull requests, code reviews, and developer workflows. This role offers the opportunity to work closely with customers, engineering, design, and go-to-market teams while shaping the future of software delivery for developers. 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: Partner with customers, developers, platform engineering teams, and internal stakeholders to understand software delivery challenges and identify opportunities to improve developer workflows. Own the product strategy and roadmap for developer-facing experiences within pull requests, code reviews, and source code management platforms. Collaborate across Software Delivery products to surface actionable insights from CI/CD Optimization, Test Optimization, Code Coverage, Code Security, Deployment Gates, Bits AI, and future capabilities. Work across source code ecosystems including GitHub, GitLab, Azure DevOps, Bitbucket, and enterprise environments to deliver scalable integrations. Partner with engineering teams to connect Datadog signals with recommendations, AI-assisted workflows, generated fixes, and future automated remediation experiences. Measure product success using customer adoption, engagement, feedback, and business outcomes while partnering with Sales, Product Marketing, Solutions Engineering, Custo

At Datadog, our Office Operations team runs the day-to-day operations to keep our employees safe, happy, and productive. This dynamic team works closely with leadership and staff to ensure that Datadog scales smoothly and continues to be a fantastic place to work. Every day brings new challenges and opportunities for collaboration and growth. What You’ll Do: Act as the face of Datadog by welcoming visitors and supporting employees in the office. Act as the primary point of contact for all in-office needs, creating a friendly, helpful, and professional environment Own and lead daily floor walkthroughs, identifying and resolving operational issues proactively to maintain a high standard of cleanliness, safety, and functionality Cultivate and maintain positive working relationships with building management & vendor partners Partner with the Security team to ensure the implementation of all safety protocols Serve as a main point of contact for incoming service tickets, ensuring timely updates, proper prioritization, and follow-through Work with vendor partners to keep the office stocked with food, snacks, and pantry supplies, ensuring everything meets our Datadog standard for quality and consistency Maintain inventory of office supplies and ensure timely restocking to support daily operations Arrange fun and engaging events for employees - both on a monthly cadence and an ad hoc basis Work closely with teammates to maintain smooth office operations and ensure consistency across all workplace processes Where required, work alongside various Operations teams to assist with office moves, build-outs and openings Who You Are: A true people person, with an empathetic and friendly demeanor A quick learner who loves tackling challenges and streamlining processes Exceptional time management skills with the ability to multitask effectively A self-starter who takes initiative and drives projects forward Calm and even-tempered, able to maintain composure under press

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. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. 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 APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially age

As a Network Engineer II on the Office Technology team, you will implement and support office network solutions across Datadog’s global offices. You will own well-scoped deployment and upgrade work, troubleshoot connectivity issues across LAN, WAN, and Wi-Fi, and partner with senior engineers on larger designs and cross-office initiatives. You will collaborate closely with vendors, Facilities, AV, IT Support, Security, and Infrastructure teams to keep Datadog offices connected, reliable, and observable. This is an IC2 role with a mix of project work and day-to-day operations. You will take ownership of clearly defined areas of the office network stack, execute production changes with care, and grow your ability to design, automate, and improve office network services with support from senior engineers. You will also use AI-assisted tools responsibly to improve troubleshooting, documentation, automation, knowledge discovery, and operational follow-through. 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: Deploy and configure network solutions for new and existing offices, including switches, wireless access points, routers, and firewalls Own scoped portions of office rollouts and upgrade projects, from planning through execution and validation Partner with ISPs, cabling providers, hardware vendors, and internal teams to turn up new services and resolve issues Troubleshoot LAN, WAN, and Wi-Fi issues using structured debugging methods, packet capture, logs, and performance data Manage routing, VLAN, firewall, and wireless configurations following team standards and change-management processes Contribute to repeatable deployment patterns through templates, documentation, scripting, or infrastructure-as-code Monitor office netwo

Databases and data stores are at the center of our applications, for legacy applications and modern AI applications alike. Yet most observability and optimization approaches lack a holistic approach or application context. Datadog has been on a mission to revolutionize how databases are operated, flipping what is often seen as a black box of complexity prone to security and performance risks, into a well oiled machine enabling our builders and businesses to move faster and smarter. We’re looking for an experienced product manager passionate about joining this mission to lead this product opportunity. 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 ambitious investments that rethink how customers operate and get value from their databases, diving into ambiguity, working with our customers on new models, and shipping new products and changes to existing products. Develop a deep understanding of our customers and their issues, what problems are really behind those issues, and how we can improve how databases are operationalized across SRE teams, DBAs and application developers. Continuously refine your understanding of database management systems and datastores from SQL and OLTP based to NoSQL e.g. AWS RDS, PostgreSQL, SQL Server, MongoDB, MySQL, etc Define, build and launch the next generation of database monitoring and optimization capabilities for our customers Join a talented engineering team with a record of disrupting observability approaches to further the mission of demystifying and optimizing databases using your team’s creativity, alongside your customers’ problems, as a key resource. Collaborate with other Product teams in Datadog to maintain and improve all Datadog products, improve the seamless integration across th

As a Senior Platform Product Manager focused on AI SDLC Trusted Throughput, you will define and drive the product strategy for enabling safe, reliable software delivery at AI-native scale across Datadog’s Internal Developer Platform. As AI accelerates development velocity and system complexity, you will help evolve SDLC systems from human-supervised workflows to platforms with built-in safety, observability, and correctness guarantees. You will partner closely with engineering, security, and developer platform teams to improve deployment reliability, operational visibility, and governance while enabling both engineers and AI agents to move quickly with confidence. This role offers the opportunity to shape foundational developer infrastructure and influence how AI-powered software delivery operates across 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: Own the product strategy, roadmap, and execution for AI-native SDLC throughput and reliability initiatives across Datadog’s Internal Developer Platform Define and drive platform outcomes aligned to DORA metrics, balancing deployment velocity with reliability, change failure reduction, and operational safety Partner with engineering, infrastructure, security, and developer experience teams to build automated validation, auditability, and risk-scoring capabilities into deployment workflows Deliver actionable SDLC observability and diagnostic capabilities that connect executive-level metrics to operational signals across the software delivery lifecycle Drive systems that monitor and validate AI-generated or AI-attributed changes to ensure correctness, compliance, and trustworthy automation Serve as a cross-functional product leader across SDLC Foundations, Security Engineering, and compl

We are seeking a highly skilled Staff IT Product Manager for Internal AI to drive the strategy, delivery, and adoption of AI-powered solutions across our enterprise IT landscape. This role will be pivotal in shaping how AI transforms our internal operations, from service delivery and knowledge management to automation and decision support. The ideal candidate has a proven track record of managing enterprise-scale AI/ML products, collaborating across IT and business functions, and delivering measurable impact. We are looking to speak to candidates who are based in San Francisco, CA or Palo Alto, CA for our hybrid working model. Key Responsibilities AI Product Strategy & Roadmap Define and execute the internal AI product strategy aligned with enterprise IT and business goals Own multiple product lines in the internal AI product space Prioritize high-value use cases across IT functions (helpdesk, infrastructure, security, applications, enterprise data) Balance quick wins (AI copilots) with longer-term bold initiatives (AI-driven automation and decision-making) Experience in implementing AI solutions for enterprises our size and scale. This should include enabling agentic platforms for organizations and bringing to the table the best practices, pitfalls and learnings from such experiences Product Management Execution Embrace the product mindset and own the lifecycle of AI products—from ideation, critical user journey definition, requirements gathering, vendor evaluation, prototyping, and implementation to scaling in production Define and manage product backlogs, roadmaps, and success metrics Drive adoption and ensure AI solutions are delivering measurable outcomes (efficiency, cost savings, user experience) Stakeholder Engagement Partner with IT leaders (Applications, Infrastructure, Security, Service Desk) to identify pain points and AI opportunities Collaborate with business stakeholders to ensure alignment and secure sponsorship for AI initiatives Communica

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

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

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 Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. 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: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Staff Integration Engineer (Workato & API Integration) to join our GTMTech team. This strategic role will lead the design, implementation, and governance of enterprise-grade integrations that power our core business processes across GTM systems, with a primary focus on Workato-based integrations and modern API management patterns. You will own the architecture for critical integration domains such as Quote-to-Cash and other high-impact GTMTech programs, ensuring our integration landscape is scalable, secure, observable, and aligned with best practices for event-driven and API-first designs. You will partner with engineering, architecture, security, and business stakeholders to define standards, mentor other integration engineers, and drive continuous improvement in how we connect systems and data. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Lead the end-to-end architecture, design, and implementation of Workato-based integrations and APIs across GTM systems (e.g., Salesforce, NetSuite, HRIS, Google Workspace) with a focus on scalability, reliability, and security Define and evolve integration standards, patterns, and best practices, including canonical integration patterns, error-handling strategies, observability, and operational runbooks Design and review complex, event-driven integration workflows leveraging technologies such as Kafka or equivalent messaging platforms, ensuring robust handling of topics, producers/consumers, durability, and retry mechanisms Drive API-first and MCP-native design for GTM integrations, leveraging RESTful APIs al

About the Role We are seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of our enterprise data landscape. This role operates at the intersection of data architecture, engineering, and AI enablement, defining solutions to integrate our Data Lake and Data Warehouse across multi-cloud platforms. Over the next 12-18 months, you will enable self-service data access and natural language query capabilities for business users. You will architect Master Data Management and data lineage frameworks ensuring AI models operate on high-quality, governed data. You will also evaluate and implement AI-powered tools to automate data quality monitoring and enhance data security. We're looking to speak with candidates based in the San Francisco Bay Area for our hybrid working model. Key Responsibilities Data Strategy & Roadmap Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy. Partner with business owners on master data governance Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness. Document trade-offs and recommend implementations for batch and near-real-time use cases Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People. Identify capability gaps and recommend technology investments with business value and effort estimates Systems Design & Solution Leadership Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification. Define requirements, lead vendor POCs, and establish integration patterns