Ai Infrastructure System Engineer Bangalore in United States

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of a best-in-class family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from a diverse group of backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a senior validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems. This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives. You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams. The Team The Rack Validation team is responsible for ensuring system readiness and quality at scale. The team works cross-functionally with firmware, silicon, and system engineering teams to validate complex AI compute platforms. Responsibilities and Duties Lead post-silicon validation of AI compute blades and racks including test planning, development, and automation. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness. Own execution against program achievements and report validation progress and risks. Triage test failures, collect debug data, and collaborate on root cause analysis. Track

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a Robotics Control Systems Engineer to take on a foundational role within our robotics team. You’ll help architect, implement, tune, and verify the control infrastructure that enables intelligent, reliable, and responsive robot behavior. This is a deeply hands-on role focused on real-time systems, actuation, dynamics, low-level hardware interaction, and whole-robot performance. You’ll spend significant time working directly with robots onsite: debugging behavior, tuning subsystems, running experiments, and providing feedback across mechanical, electrical, and software teams. This role is based in San Francisco, CA, and requires in-person 5 days a week. In this role, you will: Design and implement real-time control algorithms for robotic systems, including motion control, feedback loops, state estimation, actuator control, and subsystem tuning. Define the control architecture from low-level actuators and hardware interfaces through whole-robot behavior and policy. Identify and characterize actuator, hardware, and software parameters through rigorous experimentation, testing, commissioning, and verification. Work with machine learning engineers to implement reinforcement learning models. Collaborate across mechanical, electrical, and software teams to integrate control logic with sensing and actuation hardware. Help inform the mechanical and electrical design to maximize capability and flexibility. Create the control system architecture; determine the correct level of abstraction from actuators all the way up to whole-robot

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Software Engineers build and own high-value products for our customers and the infrastructure that lets our business scale. Vanta's team and technology surface are growing quickly, and it's essential that we invest in the right abstractions and systems to scale with our business. As a Software Engineer, you'll build and own full-stack features and platform primitives across our stack, work closely with the teams and partners who depend on what you ship, and grow into broader technical ownership. Your work will directly accelerate Vanta's growth. Our business has found incredible product-market fit and has monetized effectively since the day we signed our first customer. We're growing at a blistering pace, which presents career-defining opportunities for engineers to accelerate their growth and to contribute to a rapidly-scaling company. Visit our Vanta Engineering Blog to learn more about what our team is working on! The Integrations Platform team mission is to power the world's largest trust automation ecosystem, enabling any person or agent to build, connect, and automate trust seamlessly. We own Vanta's integration ecosystem, which currently includes over 400 integrations across Cloud Providers (AWS, Azure, GCP), Identity Providers, Mobile Device Management (MDM), and Human Resources Information System (HRIS). We are focused on developing the Integration Platform. This includes creating shared primitives for authentication, lifecycle, observability, and publishing to ensure all integrations are built on the same foundation. Our North Star is to eliminate the barrier to building integrations entirely. We aim to enable any

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time systems. You’ll love this job if you You enjoy working on distributed systems at scale and care about reliability and

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,

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

About the Team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the Role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and mea

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role Our technologies support some of the most important and impactful work in the world, including our strategic and high-impact customers in the public sector. As a Forward Deployed Security Engineer (FDSecE) you will be responsible for securing these novel applications of OpenAI’s technology. We’re looking for motivated, tenacious, and curious people who will work closely with engineering teams to ensure our infrastructure deployments are highly secure against our adversaries. As an FDSecE, you will embed directly throughout the lifecycle, working on-site and being hands-on to ensure the overall security of these deployments from design to production and through ongoing operations. This role is preferred to be based in Washington DC but may consider remote work. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel to and working from customer sites is required for this role. In this role, you will: Deeply embed with our most strategic public sector customers to implement and maintain robust security controls. Be a design and technical thought partner by leveraging security expertise on protective controls including access controls, authentication, encryption, network, and system security. Collaborate closely with teammates, cross-functional teams, customers, and service providers to achieve security and compliance goals. Ensure continuity of critical security and monitoring c

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

About the Team IT Systems Operations serves as the operational control layer connecting Security, Engineering, and Employee Technology platforms. The team ensures employee-facing systems, identity workflows, and enterprise applications operate in a predictable, governed, and continuously reliable manner as the organization scales. Beyond implementation, the team establishes structured operating patterns that ensure platform changes, access models, integrations, and lifecycle workflows evolve safely and consistently across the enterprise environment. About the Role This role acts as an operational owner for identity-connected enterprise SaaS platforms and system change controls supporting OpenAI’s compliance requirements. The engineer will be responsible for ensuring that production configuration, access models, and platform changes remain compliant, auditable, and consistently operated through defined controls. You will own and operationalize controlled system and workflow changes across identity platforms, SaaS applications, collaboration tooling, and enterprise infrastructure. You will partner closely with Security, Platform Engineering, and IT Support Operations to: Ensure identity and access workflows behave consistently across systems Implement structured rollout and configuration practices for enterprise applications Improve visibility and traceability of system changes impacting employee workflows Translate operational requirements into durable automation and policy-aligned implementations Success in this role requires not only strong engineering capability, but also sound operational judgment, disciplined documentation practices, and effective cross-functional collaboration. In this role, you will: Enterprise SaaS & Identity Platform Ownership Own administration and operational stewardship of enterprise SaaS and identity-connected platforms, ensuring configuration integrity, access governance, and compliance with defined control requirements. Own onboard

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

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. Company Overview We are building the next generation of cloud security infrastructure, focusing on advanced Data Exfiltration Protection (DXP) and unified Data Movement Policies (DMP). Our mission is to provide seamless, context-aware security that protects sensitive data without hindering developer velocity. We are looking for a visionary Principal Engineer to lead the technical strategy and architecture for our Data Movement and Perimeter control systems. Role Summary As a Principal Engineer in the Data Protection group, you will be the technical lead for the Data Exfiltration Protection (DXP) and Data Movement Policy (DMP) initiatives. You will bridge the gap between high-level security policy and low-level system enforcement, ensuring that our perimeter controls are robust, scalable, and deeply integrated with context-aware access policy frameworks. You will be responsible for the architectural evolution of our egress control systems, moving from simple IP-based rules to sophisticated, content-aware, and identity-driven data movement governance. AS A PRINCIPAL SOFTWARE ENGINEER - IDENTITY, DATA SECURITY AND TRUST AT SNOWFLAKE YOU WILL: Architectural Leadership: Lead the design and implementation of the Data Movement Policy (DMP) framework, ensuring it can handle complex

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. The Snowhouse Foundation team builds our globally distributed data warehouse. We manage a vast array of petabyte scale data sets that are continuously ingested, processed and replicated from across all Snowflake environments and external data sources. Snowhouse powers all of Snowflake’s core business, engineering and data science needs and provides customers with full visibility into their account activities, usage, and resource consumption from all their global environments. The team is investing in multiple critical areas, including a pipeline authoring platform, high performance/high efficiency data export, ingestion and data layout. Our team is also responsible for a fundamental product for Snowflake’s customers: the Snowflake system database/application that provides customers with all usage insights they need to reason about their global Snowflake footprint as well as 1st party business logic such as ML powered functions and Budgeting applications. AS A PRINCIPAL SOFTWARE ENGINEER IN SNOWHOUSE FOUNDATION, YOU WILL: Design and implement innovative highly available distributed platforms and pipelines and enhance the overall Snowflake data infrastructure Lead and drive projects from idea formulation to design, implementation and successful productionization. Collaborate

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement