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At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

As a Senior Sales Engineer at Amplitude, you'll be the technical quarterback for our most strategic opportunities. You'll partner with Account Executives to win complex, multi-stakeholder deals by translating product capabilities into business outcomes that matter to Product, Marketing, and Analytics leaders. You'll lead technical discovery, architect custom proof-of-concept implementations, and serve as a trusted advisor to prospects navigating their digital analytics strategy. Your technical credibility and business acumen will directly influence the annual pipeline. What You'll Do Deal Execution (70% of time) Lead technical evaluation phases for deals ranging from 100K to 1M+ ARR Conduct deep discovery to map prospect workflows, tech stack dependencies, and decision criteria to Amplitude's differentiation Design and execute hands-on proof-of-concepts that prove value within the prospect's actual data and use cases Handle technical objections related to data architecture, privacy/compliance, and integration complexity Present to C-level executives and translate technical capabilities into ROI narratives Internal Collaboration (20% of time) Partner with Product Management to communicate feature gaps and customer requirements that affect deal velocity Work with Customer Success to ensure smooth handoffs and technical alignment during implementation Mentor junior SEs on technical positioning and demo best practices Thought Leadership (10% of time) Contribute to our competitive intelligence on tools like Google Analytics 4, Adobe Analytics, and Mixpanel Develop reusable demo assets, technical content, and proof-of-concept frameworks for the broader SE team What We're Looking For Required 5+ years in software pre-sales (SE, Sales Consulting, or technical Account Management roles) You must be comfortable speaking to nuanced technical concepts and be a self-learner (examples include: Python, SQL, hyperscaler integrations, APIs, R) Hands-on SQL experience: you can write j

Senior -Power and Performance Validation Engineer 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 an elite 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 diverse 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 Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to deb

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. 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: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities: Contribute to the development of new product opportunities by assisting with the overall Verification Activities of DRAM Design Actively leverage AI‑based tools, agentic workflows, and automation frameworks to: Accelerate verification cycle time Assist in Test-Case/TB and various other components required for DRAM Design Verification Improve debug efficiency across simulation and silicon learning loops Provide verification support to design projects by simulating, analyzing, and debugging pre-silicon block level/full chip designs. Develop Test cases/Stimulus to increase the functional coverage for all DRAM and emerging memory architectures and features Develop and maintain test benches / test vectors using simulation tools and run regressions for coverage analysis and improvements using Agentic AI Flow Hands on experience in SV, UVM based Verification. Good scripting skills using perl, python is a plus Good understanding of digital / mixed signal circuits and experience in Digital /Mixed signal Verification. Understand the usage of industry standard tools like Virtuoso, Xcellium, Simvision, vsim, Waveview, Finseim, Hspice and Micron-specific simulators Collaborate with CAD, EDA, and software teams to integrate AI‑driven flows into simulation, verification, and design sign‑off environments and contribute to cross-group communication to work towards standardization and group success About

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior Data Engineer, you will design and build scalable data pipelines and data infrastructure that power Smart SMS features, including SMS categorization, fraud detection, spam intelligence, and AI-driven capabilities. You will work closely with Data Scientists, Data Analysts, and Product teams to develop robust data platforms, enable feature engineering for ML models, and deliver reliable datasets that drive product insights and decision-making for over a million daily users. What you'll do: Maintain and improve the ingestion pipeline to reliably deliver billions of events daily within defined SLAs Provide support for all teams in building and optimizing their complex pipelines Work closely with other teams to identify pain points and problems around the platform Develop new tools and frameworks to improve the data platform Facilitate a company-wide, data-driven culture Work in close collaboration with data scientists and data analysts to help support their work going into production Work on large-scale projects such as building an ML platform and streaming use cases Set up best practices and processes around software and data development What you b

Overview: Guidepoint's Engineering team thrives on delivering innovative technology solutions that accelerate revenue growth, reduce costs and increase efficiency and productivity. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to create new products and improve existing platforms to optimize the seamless delivery of our services. This is a hybrid position based in Pune. What You’ll Do: Design, build, and maintain a test automation framework. Automate test cases and design, develop, and execute reusable and maintainable automated scripts. Analyze issues related to automated and/or load testing, research and propose solutions, and add, modify, or enhance previously recorded automated scripts. Analyze test results and determine root causes of issues. Determine severity and scope of issues to guide prioritization for resolution. Provide regular software defect tracking and regression updates and present status and technical reports as required. Assist in planning, developing, and delivering training related to automated test tools and frameworks. Review, establish, and maintain thorough documentation, templates, and process improvements and communicate technical issues to engineering leadership and business stakeholders. Work closely with other engineering team members and departments on technical issues and updates. Keep abreast of technology trends and advancements within areas of specialization and incorporate improvements into the overall testing process. What You Have: 7+ years of experience in QA Automation engineering is a must. Experience with writing test scripts from scratch for manual testing Strong experience in automated testing practices and tools — Playwright/Selenium/Cypress/Any Othe

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking a Staff DB SRE to build the runtime foundation for NVIDIA’s enterprise AI platforms — with a strong emphasis on database infrastructure at scale. This role blends large-scale database transformation with the building and development of GPU-accelerated platforms. You'll develop the software systems, automation frameworks, and high-performance database services that power NVIDIA’s AI workloads at scale. What you'll be doing: Design and operate highly available database clusters (MySQL, MSSQL, Oracle) with automated replication, failover, point-in-time recovery, and disaster-recovery strategies at enterprise scale. Drive database performance engineering — own query optimization, indexing strategies, connection pooling, lock-contention analysis, and storage-engine tuning for production systems handling millions of transactions. Build self-service database lifecycle automation — from one-click cluster provisioning and schema migrations to zero-downtime upgrades, blue-green deployments, and automated capacity scaling. Bridge relational and AI-native data infrastructure — extend traditional database exper

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you’ll be doing: Use and develop AI-powered tools to make software testing smarter, faster, and more effective! Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. Work with product, engineering, and cross-functional teams to review requirements and define test strategies. Build test plans, design and execute test cases, and report quality status, risks, bugs, and results. Perform functional, performance, fault-injection, reliability, and regression testing for cloud-native systems. Automate test cases and contribute to scalable test frameworks. Manage the bug lifecycle, reproduce customer issues, and verify fixes. What we need to see: MS or PhD in Computer Science, Engineering, or a related field. 5+ years of QA, test automation, or software testing experience. Hands-on experience using AI tools to improve QA workflows. Strong QA fundamentals, test strategy, test planning, and failure analysis skills. Proficiency with Unix/Linux and shell or Python programming. Exp

About the Role At Together AI, you'll own the systems and tooling that let our engineers ship quickly and reliably: CI/CD pipelines, release infrastructure, local dev environments, and the testing systems the whole engineering team depends on. This is a high-leverage, build-heavy role. You'll take on big projects and drive them end to end: building a full-stack release service with deployment orchestration, rebuilding the front-end build pipeline, standing up testing infrastructure that kills flaky builds. The goal is straightforward: engineers should spend their time building products, not fighting their tooling. This is an engineering role focused on building systems, not a QA or manual testing role. You build the infrastructure that makes manual effort unnecessary. Responsibilities Build and own the production systems engineers rely on: release services with deployment orchestration (canary, blue/green), reusable CI/CD pipelines, and self-service tooling. Build testing infrastructure: the frameworks and harnesses that make tests fast and reliable, and track down flaky tests and slow builds at the systems level. Build and maintain local dev environments and containerized workflows so engineers can spin up and iterate fast. Create starter templates and shared tooling (CLIs, codegen, IDE integrations) so teams can stand up new services in minutes. Be the go-to engineer for GitHub Actions and GitOps: defining problems, untangling pipeline issues, and improving how the org works with them. Improve front-end build tooling and developer workflows alongside product engineers. Work across the org to find the biggest sources of friction and fix them at the root. Document what you build so others can use it. Requirements 5+ years building software in production, with a strong track record of owning systems or services end to end, from design through operation. Strong software engineering fundamentals. You write production-quality code and have built and operated real servic

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. We’re looking for a Senior AI/Computer Vision Engineer to build AI systems end to end, from defining the problem and data requirements to training models, validating them, deploying on edge devices, and integrating them into C++ pipelines. This is a hands-on engineering role for someone who can take applied AI projects from concept to production and is comfortable working across modeling, evaluation, deployment, and system integration. Responsibilities: Own AI and computer vision projects end to end, from technical definition to production deployment; Translate product needs into system, data, model, and evaluation requirements; Define data collection, annotation, and validation strategies; Train and optimize deep learning models for real-world vision and multimodal applications; Build testing, benchmarking, and failure analysis workflows; Optimize models for edge devices with attention to latency, memory, throughput, and accuracy tradeoffs; Integrate models into production inference systems, including C++ edge pipelines; Work closely with software and product teams to ship reliable AI features at scale. Requirements: MS or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience; Strong Python skills; Solid experience with PyTorch, TensorFlow, or similar frameworks; 4+ years of expe

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. We’re looking for a Senior AI/Computer Vision Engineer to build AI systems end to end, from defining the problem and data requirements to training models, validating them, deploying on edge devices, and integrating them into C++ pipelines. This is a hands-on engineering role for someone who can take applied AI projects from concept to production and is comfortable working across modeling, evaluation, deployment, and system integration. Responsibilities: Own AI and computer vision projects end to end, from technical definition to production deployment; Translate product needs into system, data, model, and evaluation requirements; Define data collection, annotation, and validation strategies; Train and optimize deep learning models for real-world vision and multimodal applications; Build testing, benchmarking, and failure analysis workflows; Optimize models for edge devices with attention to latency, memory, throughput, and accuracy tradeoffs; Integrate models into production inference systems, including C++ edge pipelines; Work closely with software and product teams to ship reliable AI features at scale. Requirements: MS or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience; Strong Python skills; Solid experience with PyTorch, TensorFlow, or similar frameworks; 4+ years of expe

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each brings together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are searching for a highly motivated engineer to lead performance benchmarking and optimization efforts for our data center products. You will be instrumental in ensuring our data center solutions deliver industry-leading performance for accelerated computing workloads. What you will be doing: Design and execute comprehensive performance benchmarking strategies for our data center platforms and products Characterize real-world AI training, inference, and HPC workloads at scale Define, track, and report key performance indicators (throughput, latency, efficiency, scaling) Build automation tools and frameworks for performance monitoring and analysis Identify and analyze performance bottlenecks across compute, memory, network and storage subsystems Work closely with architecture, hardware,

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines