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Ai Infrastructure System Engineer Bangalore in United States

5,082 active opportunities · Updated October 2026

Explore current ai infrastructure system engineer bangalore jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Santa Clara, United States
✓ High-confidence listingCompany trend -8%
Quick readStrong listing-quality and freshness signals

We are seeking a highly skilled and hard-working Senior Test Developer / test engineer to join our multifaceted Enterprise Software QA team. This role offers an outstanding opportunity to leave your mark on the design, construction, optimization and testing of large-scale infrastructure for various foundational NVIDIA unified cloud services and data center offerings. If you are a dedicated engineer with strong expertise in cloud infrastructure and distributed systems and want to apply your skills with AI tools, this role could fit you perfectly. You will thrive in an exciting, innovative environment. What you'll be doing: Work with development teams on test plans for all layers of SW stack for cloud infrastructure, execution, reviews, failure analysis and assessing overall quality and risk. Work with customer PMs on software issues including technical feedback from OEMs and CSPs. Develop key benchmarks to track execution and deploy process improvements to improve efficiency Leverage AI skills to expedite the test scope, test plan, execution and automation workflows. Lead NVIDIA Cloud and Data Center bring up activities which will involve validation, reporting, working with engineering to debug issues, providing design input at times, adding coverage in different areas. Design, develop and maintain CI/CD pipelines for continuous testing in cloud environments when needed. Perform performance, scalability, and reliability testing of cloud services. Implement and maintain test environments in cloud platforms such as AWS, Azure, or Google Cloud. Supervise the infrastructure to alert on significant events, ensuring the highest level of system performance and reliability. Work with various different partner teams to ensure availability of clusters to test on and take the lead in resolve all issues. Working with tea

AWSAzureDockerKubernetes
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📍 Remote, United States· Remote
✓ High-confidence listingCompany trend -8%
Quick readStrong listing-quality and freshness signals

NVIDIA DGX Cloud is an AI Factory designed to power the next generation of AI and industrial-scale breakthroughs. As a Principal Engineer for Security Architecture, within our Security Engineering organization, you will own a core security domain of the AI factory: the architecture, the paved road that delivers it, and much of the code underneath. You will hold the security design bar across DGX Cloud from inside the teams doing the building, and this is a founding seat on a new team. Security Engineering is a new organization at DGX Cloud, accountable for the security outcome of the platform, and Security Architecture is the function inside it that holds the design bar. Security here is fleet horizontal and stack vertical, so your work will cross every DGX Cloud engineering organization: you will embed with the teams building GPU clusters, control planes, and services, join their designs as a participant rather than an approver, and leave behind systems in which an entire class of risk is no longer possible. There is no architecture review board here and no approval queue. You are a senior IC with deep security domain knowledge, and the security bar holds because you helped set it and then helped ship it. What You Will Be Doing: Own a Security Domain End to End: Take architectural ownership of a core domain of DGX Cloud security, from the design through the system running in production. That could be tenant and GPU workload isolation, workload identity, infrastructure and network, supply-chain provenance, hardened baselines and patching, or deploy-time policy and admission control. Embed with the Teams Building It: Join the design early, write the code, and help land it. The posture is not "you did this wrong." It is "here are the considerations we need to meet, I will help, let's go to work." Build Paved Roads, Not

KubernetesLinuxArtificial IntelligenceAI
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📍 New York, New York, United States· Full-time· Remote
✓ High-confidence listingCompany trend -72.3%
Quick readStrong listing-quality and freshness signals

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

PythonAWSMachine LearningAI
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📍 New York, NY, United States· Full-time
✓ High-confidence listingCompany trend -87.9%

$190.4K – $285.6K/yr

Quick readStrong listing-quality and freshness signals

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Lead the technical design and architecture of major platform initiatives, author design documents and build consensus across engineering teams. Define technical roadmaps for complex, multi-quarter projects that span multiple teams. Make critical architectural decisions for company documentation infrastructure, balancing scalability, reliability, and developer experience. Evaluate and set direction for integrating emerging technologies, including AI/LLM capabilities, into company documentation platforms and authoring tools. Establish and evolve engineering standards, best practices and technical guidelines for the team and broader organization. Partner with engineering teams across the company to understand documentation needs and design integrated solutions. Design, build and maintain scalable, reliable and performant services and systems. Contribute high-quality code across the full stack and navigate codebases with different languages and tools. Debug and resolve complex production issues and improve system reliability. Take ownership of system health and incident response. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Software Engineering, Engineering, or a related field, plus four (4) years of experience in Software Engineering. Must have four (4) years of experience in each of the following: - Working in a full stack environment with a foc

TypeScriptJavaMongoDBAI
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -79.1%
Quick readStrong listing-quality and freshness signals

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 ship AI products. THE ROLE The largest, most demanding enterprises run on Baseten, and they bring exacting requirements for how people, services, and agents access the platform. This is the founding role for our identity and authorization team within enterprise engineering. You'll own the identity and access layer of the Baseten platform: the authorization model, credential systems, and admin experiences that enterprise IT teams use to govern access for organizations like Harvey, HubSpot, and Notion. You'll design and build Baseten's fine-grained authorization system from the ground up to support the workflows customers depend on today while giving them cleaner, more precise ways to manage access as the platform grows. Authorization at Baseten requires low-latency permission checks at high request volume, consistent contracts and behaviors across the product suite, and strong security guarantees for mission-critical, highly regulated workloads. EXAMPLE INITIATIVES Recent and upcoming work in this area: Fine-grained authorization for users, service accounts, and agentic workloads: per-resource permissions at the organization, team, and workload scope to support both common workflows and complex enterprise access policies Programmatic authentication allowing high-compliance customers to connect service principles securely via short-lived, workload-based credentials Agent credentials that grant an agent exactly the access it needs for the gi

PythonKubernetesMachine LearningAI
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

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 As a Software Engineer on the Internal Tooling team, you will own the internal operating system that sits at the heart of how Baseten operates. Capacity helps unlock revenue by carefully balancing supply and demand. The operating system manages all aspects of the customer lifecycle: from onboarding to managing complex customer SLA requirements. This role is for engineers who want to own a product end to end, not just implement tickets. You will work directly with the Capacity, Sales, and Engineering teams to understand requirements, define solutions, and ship software that removes friction from some of the most high-stakes workflows in the company. If something is slow, manual, or error-prone in the capacity fulfillment lifecycle, you will be the one to fix it. You are a strong fit if you have strong product intuition, move fast without sacrificing quality, and take satisfaction in building tools that make the people around you measurably more effective. RESPONSIBILITIES Own the Capacity product end to end: scoping, design, implementation, and iteration based on feedback from internal stakeholders Translate complex operational requirements from Capacity, Sales, and SRE teams into clean, ergonomic product experiences Build and maintain full-stack features across the Capacity toolchain, including UI surfaces, APIs, and backend services Identify workflow bottlenecks and manual processes across the capacity lifecy

JavaScriptJavaAWSRest
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

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. At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations. THE OPPORTUNITY Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed. In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts. WHAT YOU'LL DO Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack,

PythonKubernetesMachine LearningAI
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📍 New York, New York, United States· Full-time
✓ Quality checkedCompany trend -72.3%

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid's Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget

AWSKubernetesAIGo
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -72.3%

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role You will develop security capabilities to secure Plaid infrastructure and to secure sensitive data access. You will own, maintain, and build Plaid’s security infrastructure and services like Key Management System and Secure Token Service. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in their own products and services. You will assist with Plaid’s incident response and security awareness pro

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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -84.7%

From $192K/yr

Quick readStrong listing-quality and freshness signals

Senior Software Engineer - Streaming Platform Client Data streams are mission-critical at Datadog, powering near real-time communication across the vast majority of our services. Our Streaming Platform group builds the core infrastructure and abstractions that ensure Datadog remains a trusted partner for engineers worldwide. See our blog post . The Streaming Platform Client team sits at the heart of this ecosystem. We own the Rust client library (producers and consumers) with language bindings for Java, Go, and Python. We focus on building intuitive APIs and abstractions that make a powerful distributed system easy to adopt and operate for the hundreds of internal users of our library. Our library runs on critical data paths that handle hundreds of millions of messages per second making performance, observability, and reliability paramount. We also develop and operate the service that bridges the clients fleet with the platform's control plane, handling complex balancing, scaling, and static stability challenges. We are seeking a Senior Software Engineer to help us evolve these features. You will collaborate directly with our users, tackle performance-critical code, and solve complex distributed systems challenges across the control plane, client libraries, and data plane. 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: Work within a distributed, high-impact team spanning Europe and the US, building critical technologies that power data pipelines for dozens of internal teams and hundreds of services. Architect and implement resilient interactions between our client libraries and the control plane. Optimize our high-throughput, low-level streaming library to push the boundaries of performance and efficiency. Champion the developer experience by providing

PythonJavaGitAI
D
📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -84.7%

From $192K/yr

Quick readStrong listing-quality and freshness signals

Senior Software Engineer - Streaming Platform Client Data streams are mission-critical at Datadog, powering near real-time communication across the vast majority of our services. Our Streaming Platform group builds the core infrastructure and abstractions that ensure Datadog remains a trusted partner for engineers worldwide. See our blog post . The Streaming Platform Client team sits at the heart of this ecosystem. We own the Rust client library (producers and consumers) with language bindings for Java, Go, and Python. We focus on building intuitive APIs and abstractions that make a powerful distributed system easy to adopt and operate for the hundreds of internal users of our library. Our library runs on critical data paths that handle hundreds of millions of messages per second making performance, observability, and reliability paramount. We also develop and operate the service that bridges the clients fleet with the platform's control plane, handling complex balancing, scaling, and static stability challenges. We are seeking a Senior Software Engineer to help us evolve these features. You will collaborate directly with our users, tackle performance-critical code, and solve complex distributed systems challenges across the control plane, client libraries, and data plane. 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: Work within a distributed, high-impact team spanning Europe and the US, building critical technologies that power data pipelines for dozens of internal teams and hundreds of services. Architect and implement resilient interactions between our client libraries and the control plane. Optimize our high-throughput, low-level streaming library to push the boundaries of performance and efficiency. Champion the developer experience by pro

PythonJavaGitAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

PythonSQLAWSAzure
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team OpenAI's Industrial Compute organization is responsible for planning, delivering, operating, and optimizing the compute infrastructure that powers frontier AI. As OpenAI scales toward becoming an intelligence utility, Industrial Compute coordinates a complex lifecycle spanning infrastructure strategy, capacity planning, provider partnerships, fleet operations, product demand, and financial planning. The organization manages one of the largest and fastest-growing compute footprints in the world, where decisions around capacity allocation, deployment readiness, utilization, reliability, and product demand directly impact product availability, customer experience, and business performance. The Capacity Systems team builds the software platforms, data systems, and automation frameworks that connect these functions into a shared operating model. We transform fragmented planning workflows into scalable systems that enable teams to understand what compute was contracted, delivered, healthy, allocated, and ultimately converted into business and research outcomes. About the Role We are seeking a Capacity Systems Software Engineer to build the platforms and services that power Industrial Compute planning, forecasting, optimization, and operational decision-making. In this role, you will design and develop software systems that connect infrastructure delivery, fleet health, capacity allocation, demand forecasting, deployment readiness, financial planning, and product consumption into a unified system of record. Your work will help OpenAI make better decisions about where compute should be deployed, how capacity should be allocated, and how infrastructure investments translate into business value. You will partner closely with Capacity Planning, Fleet Operations, Infrastructure Engineering, Product, Finance, Supply Chain, and Strategic Sourcing teams to replace spreadsheet-driven workflows with scalable software systems that enable visibility, automation, and dec

TypeScriptPythonJavaSQL
O
📍 United States· Full-time
✓ Quality checkedCompany trend -80.2%

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 We’re seeking an exceptional Staff - Principal level offensive security domain expert to build agents that continuously identify and coordinate remediation of vulnerabilities across OpenAI’s infrastructure and applications. You will be the technical owner of this effort, combining deep offensive security judgment with agent engineering to build a production system that can operate safely and reliably at scale. As OpenAI increasingly uses automation throughout the company, we believe our security testing must become increasingly automated as well. Advances in model capabilities create an opportunity to test more of our attack surface than would be possible through human effort alone and a need to ensure that we remain ahead of those same capabilities as they become available to attackers. In this role, you’ll build a portfolio of specialized agents that develop a deep understanding of OpenAI’s infrastructure, applications, processes, and security boundaries. These agents will combine internal context with feedback from running systems to explore our cloud environments, Kubernetes clusters, web applications, endpoints, external attack surface, and other high-value targets. The goal is for agents to not only discover vulnerabilities, but also to validate exploitability, document impact, drive remediation, and verify fixes. Success will be measured through outcomes like vulnerabilities fixed, attack surface covered, and performance on evals

AWSKubernetesLinuxRest
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -72.4%
Quick readStrong listing-quality and freshness signals

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 A strong and reliable platform is essential to scaling Sentry for the future. Our Platform organization is responsible for everything that powers Sentry—from cloud infrastructure and streaming systems to storage, deployment, and security. We own the core services and technical foundations that enable every product and engineering team at Sentry to move fast and build with confidence. We're looking for a passionate and pragmatic Senior Staff Software Engineer to help lead this evolution. In this role, you’ll report directly to the VP of Engineering and collaborate with teams across the company to shape the future of Sentry’s platform. What You’ll Do Architect the future of Sentry by translating business needs and product strategy into clear, scalable technical blueprints. Partner with product and engineering leaders to align technical roadmaps with company goals. Lead cross-cutting initiatives across the Platform org—owning them end-to-end and driving meaningful outcomes. Promote engineering excellence by mentoring platform engineers, sharing best practices, and setting high standards for system design, scalability, and operational quality. Review major architectural proposals and help ensure consistency, maintainability, and long-term technical health across the company. You’ll Love This Job If You... Enjoy designing and building platforms that help teams move faster and scale safely. Thrive on solving complex, multi-dimensional problems across product, infrastructure, and organizational layers. Want to make architectural decisions that shape Sentry’s long-term success. Bring new ideas, tools, and frameworks t

AWSGCPKubernetesAI
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