Ai Infrastructure System Engineer Bangalore in New York

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're looking for a People Operations Generalist to join our growing People team. You'll touch the employee lifecycle end-to-end — from offer acceptance through offboarding — while helping to build the processes and documentation that let our People function scale with the business. This is a great fit for a highly organized, systems-oriented people person who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. What you’ll do Own and continuously improve the new hire onboarding experience, ensuring employees are set up for success and internal tasks are tracked and completed on time. Serve as a first point of contact for employee questions across the full HR spectrum, triaging and routing more complex issues to the right People team member or external partner. Maintain and improve self-service resources (FAQs, Not

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 PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

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're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

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're hiring a VP of Finance to build the finance function from the ground up as our first full-time finance hire. This is a high-impact role for someone who thrives at the intersection of strategic thinking and hands-on execution. We are looking for someone who can architect the systems and processes that will scale with Modal, partner closely with the founders and executive team, and grow into the company's CFO. You'll report directly to the CEO and collaborate closely with our BizOps, GTM, and Product teams. In this role, you will: Build and maintain Modal's operating model, tying financial performance to company KPIs and resource allocation Lead all budgeting, forecasting, and long-range planning processes, and develop the reporting infrastructure that gives leadership and the board clear, timely visibility into the health of the business Partner with the found

As the Senior Product Manager for the Actions & Automations team, you will own the ecosystem that enables customers, partners, and Datadog teams to build, deploy, and operate AI agents on Datadog. You will drive the strategy and execution for the platform capabilities, developer experience, integrations, and extensibility model that make Datadog the best place to build agents that understand and act on production systems. Modern engineering organizations are entering a new era where software is not only monitored and operated by humans, but increasingly by AI-powered agents. As agentic workflows reshape how teams build, operate, secure, and troubleshoot systems, customers need a platform for creating specialized agents, connecting them to business and engineering systems, governing their behavior, and extending them to solve unique organizational problems. You will define and build the ecosystem that makes this possible. Agent Builder sits at the intersection of Datadog's products, AI capabilities, and ecosystem strategy. You will have the opportunity to work across the breadth of the Datadog platform, partner with teams throughout the company, and help establish Datadog as the foundation for operational AI. 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 vision, strategy, and roadmap for Datadog's Agent Builder platform and ecosystem. Own the core platform capabilities that enable customers and partners to create, customize, deploy, and manage AI agents. Drive the extensibility model for agents, including integrations, tools, actions, context sources, APIs, SDKs, and developer workflows. Shape how agents perform actions across Datadog products and third-party systems. Partner closely with AI, platform, infrastructure, and product tea

About Datadog: Datadog is the essential monitoring and security platform for cloud applications. We bring together end-to-end traces, metrics, and logs to make your applications, infrastructure, and third-party services entirely observable. These capabilities help businesses secure their systems, avoid downtime, and ensure customers are getting the best user experience. The Team: The Financial Planning & Analysis (FP&A) team analyzes company financial data (revenue, customers, headcount, expenses, etc.) in order to support the business’ growth and success. Within FP&A, the R&D Finance team enables the financial strategy behind Datadog’s Engineering and Product organizations. We partner directly with technical leadership to drive decision-making around our most critical investments. Your work will be highly cross-functional and play a pivotal role in connecting the dots across the organization through a financial lens, ensuring operational alignment and informing decision making. The Opportunity: As a part of the R&D Finance team, this person will be key in supporting our product and engineering leadership team. Reporting to the Senior Manager, you will help create our annual budget and financial targets and work with operational leaders to support execution against our goals. Your work will be highly cross-functional and strategic, and you will play a pivotal role in connecting the dots across the organization through a financial lens, in order to help ensure operational alignment and inform decision making. What You’ll Do: Partner with senior business leaders to manage their departmental budgets on a regular basis, including but not limited to the company’s co-founder and CTO Manage financial forecasts and analytics, which include data across revenue, customers, product, company expenses, and headcount / workforce. Help manage significant portions of the company’s spend, including but not limited to AI and GPU spend across the compan

The GTM Enablement & Business Value Excellence team is the center of excellence responsible for how go-to-market execution is designed, enabled, measured, and continuously improved across Sales Enablement, Technical Solutions Enablement, and Business Value. We establish the capabilities, operating model, systems, analytics, and governance that enable our customer-facing teams to execute consistently at scale and adapt as our business evolves. Within the team, Enablement Operations designs and manages the operational infrastructure that powers enablement at scale. This includes operational governance, enablement systems, knowledge management, reporting, operational processes, and continuous improvement, ensuring programs can be delivered consistently, measured effectively, and continuously optimized. The Opportunity: As an Enablement Operations Manager, you will own the operational infrastructure that enables our programs to run efficiently and consistently at scale, with a primary focus on supporting Technical Solutions Enablement. You will partner closely with the Technical Solutions Enablement team to manage operational processes, enablement systems, knowledge management, reporting, governance, and continuous improvement. You will also collaborate with the Enablement Systems & Analytics team and cross-functional stakeholders to evolve the operational capabilities that support scalable execution. This role is ideal for someone who enjoys building scalable systems and processes, improving how work gets done, and creating the operational foundation that enables high-performing teams. 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: Support the operational processes, governance, and enablement systems that support Technical Solutions Enablement. Man

We are looking for a Program Manager to join our People Team, reporting to the Chief of Staff to the Chief People Officer. In this role, you will drive large-scale, high-impact, and cross-functional programs that shape and evolve our People products and infrastructure. You will operate at both a strategic and executional level, partnering across the People Team, and with business and functional stakeholders across Finance, Legal, IT, and business leadership to deliver transformative initiatives that support Datadog’s growth. This is a highly visible role requiring strong program management, systems thinking, and the ability to connect initiatives across the organization while improving operational effectiveness and employee experience. 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 end-to-end delivery of complex, cross-functional People programs, from ideation through execution and iteration Partner with senior stakeholders across the business to define program goals, success metrics, and roadmaps Deliver People products through scalable processes and frameworks that improve employee experience and organizational effectiveness Identify dependencies, risks, and tradeoffs across initiatives, proactively driving alignment and decision-making Translate strategic priorities into actionable plans, ensuring clear communication and accountability across teams Establish program governance, reporting, and operating rhythms to track progress and outcomes Synthesize insights across multiple workstreams to inform executive-level updates and recommendations Continuously improve program management practices within the People Team Who You Are: 5+ years of experience in program management, operations, consulting, or a related field, preferably

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. 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: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

Datadog's integrations are the connective tissue between our platform and the technologies our customers run in the real world. As a Sr. PM on the Agent Integrations team, you will own the vision, prioritization, and execution for 100+ integrations that run directly inside the Datadog Agent from foundational infrastructure (MySQL, Kafka, Kubernetes) to the rapidly growing landscape of self-hosted AI and on-premise enterprise technologies. This is a high-impact, breadth-first role at the intersection of infrastructure observability and the frontier of AI-native workloads. At Datadog, we place value in our office culture; the relationships it builds, the creativity it brings, and the collaboration of being together. 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 Agent Integrations roadmap. Determine which new integrations to build and which existing ones to improve, balancing customer demand, business impact, and engineering capacity across a catalog of 100+ technologies. Drive the expanding AI integration surface. Lead product strategy for self-hosted AI workloads, including LLM inference frameworks (e.g., Hugging Face TGI, BentoML), AI agents, MCP servers, and model orchestration tools, so Datadog customers can monitor every layer of their AI stack. Expand on-prem and hybrid coverage. Prioritize and execute new integrations for on-prem technologies including storage systems, HPC schedulers, network devices, and legacy enterprise platforms where customers run critical workloads. Build observability for ERP systems. Define and drive Datadog's strategy for monitoring enterprise ERP platforms (SAP, Oracle EBS/Fusion, Microsoft Dynamics) covering performance, job execution health, and integration layer telemetry so enterprise customers can observe their ERP stack alongside the rest of their infrastructure. Analyze adoption and customer feedback at scale. Use data from multiple sources to

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a technical, data-driven Product Management leader to own CLEAR's Marketing Technology platform. This role is responsible for the systems, data, and measurement capabilities that power member acquisition from first touch through enrollment. You will own CLEAR's MarTech ecosystem, including attribution and tracking, audience data infrastructure, CRM and lifecycle marketing platforms, and the integrations that connect marketing signals to actionable insights. Partnering closely with Marketing, Engineering, and Data teams, you'll ensure CLEAR has the tools and intelligence needed to scale growth across paid, organic, and partner channels. What You'll Do: Own the vision, roadmap, and performance of CLEAR's MarTech ecosystem, including CRM, audience activation, tracking, attribution, and marketing data infrastructure. Build best-in-class measurement capabilities across paid, organic, and partner channels, creating a trusted source of truth for acquisition performance. Partner with Marketing to improve audience targeting, lifecycle messaging, SEO/SEM performance, and channel optimization. Drive strategy for audience segmentation, activation, suppression, and first-party data utilization using platforms such as Snowflake and Hightouch. Own the digital enrollment experience, ensuring it is optimized for conversion, personalization, and growth. Define success metrics, manage vendor relationships, and prioritize investments that maximize marketing effectiveness and ROI. What We're Looking For: 8+ years of Product Management experie

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About the Team Postman is the world’s leading API platform, used by millions of developers and thousands of organizations to design, build, test, and operate APIs that power modern software. As APIs become the backbone of digital business and AI-driven systems, enterprises rely on Postman to ensure the quality, security, and governance of the APIs that run their most critical applications. Financial services has emerged as one of Postman’s fastest-growing and most strategic customer segments. Banks and financial infrastructure providers are increasingly building platform businesses powered by APIs, enabling everything from payments and open banking to embedded finance and AI-driven services. To accelerate our momentum in this market, we are launching our first vertical-focused sales team dedicated to financial services. We are looking for a Head of Financial Services, Americas to build and lead this effort. This is a senior leadership role reporting directly to the Chief Revenue Officer, based on the East Coast (preferably New York City or Boston). The Opportunity You will lead Postman’s enterprise sales team for the

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. CLEAR is seeking a Senior Security Operations Analyst III to join our SOC team to help strengthen our ability to detect, investigate, and respond to evolving security threats. In this role, you’ll lead complex investigations, improve CLEAR’s threat detection and response capabilities, and serve as a trusted security partner while helping develop the analysts and program around you. What you'll do: Lead complex investigations of security events across corporate networks, endpoints, data centers, cloud environments, and other critical systems, driving incidents from initial analysis through escalation and remediation Develop, tune, and optimize threat detection logic across SIEM, EDR, and other security platforms, proactively identifying coverage gaps, reducing false positives, and improving the fidelity of security alerts Partner with Engineering, Infrastructure, and other teams to investigate threats, identify root causes, communicate risk, and drive timely remediation and improvements to CLEAR’s security posture Apply threat intelligence, data, automation, and AI-enabled tools to identify emerging attack patterns, accelerate investigations, improve detection workflows, and strengthen decision-making while applying sound security judgment Serve as a subject matter expert and escalation point for other analysts, mentoring junior team members, sharing knowledge, and helping establish scalable processes, playbooks, and standards for threat detection and analysis Continuously evaluate CLEAR’s detection coverage against the evolving t