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We are seeking a Staff Site Reliability Engineer to join our growing Gurugram Products & Technology team to provide technical direction, shape architecture, and build key operational foundations of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Site Reliability Engineer on this new team, you will be responsible for providing technical leadership for the operational foundations that enable deployment at scale of AI applications. You will own the reliability architecture of the platform as it expands across regions and cloud providers, and set the technical direction for how the platform is operated, including capacity planning, multi-cloud expansion, incident response, and SLO discipline. The platform's SRE team owns the operational foundations: the Kubernetes fleet, networking, observability and alerting, and tenant isolation. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Position Expectations Own the reliability architecture of the platform across regions and cloud providers Collaborate with the teams building the platform, providing internal support and guidance on operability, capacity, and best practices Set operational standards for the team: on-call quality, incident response, SLO discipline Mentor and technically develop the SRE team Participate in a 24/7 on-call rotation to resolve issues involving platform infrastructure Qualifications 10+ years of experience working on software and operating distributed systems, with deep Kubernetes expertise, including designing or evolving multi-cluster platforms Proficiency in Python, Go, or a similar programming language Understand workload isolati

We are seeking a Senior Site Reliability Engineer to join our growing Gurugram Products & Technology team to provide technical direction, shape architecture, and build key operational foundations of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Senior Site Reliability Engineer on this new team, you will be responsible for enabling deployment at scale of AI applications and improving the performance, scalability, and reliability of the distributed systems infrastructure for this new product. The platform's SRE team owns the operational foundations: the Kubernetes fleet, networking, observability and alerting, and tenant isolation. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Operate and improve the multi-tenant Kubernetes infrastructure that runs customer workloads Build for reliability, making services and infrastructure available, resilient, fault-tolerant, and self-healing Identify and configure key metrics to detect incidents and quantify service health, availability, and performance Participate in a 24/7 on-call rotation to resolve issues involving platform infrastructure Mentor early-career SREs and contribute to the team’s operational practices as it grows Qualifications Strong background in software development and operating distributed systems 6+ years of experience building and operating distributed systems, with proficiency in Python, Go, or a similar programming language Experience operating Kubernetes in production and debugging below the abstraction layer, including scheduling, cluster networking, and node-level issues Expertise in cloud infrastructure platforms, in

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Designs, builds, and maintains large-scale data infrastructure and data processing systems. Implements robust and scalable solutions to support data-driven applications, analytics, and business intelligence. What you will do Ensures seamless integration of data from different sources, such as databases, application programming interfaces (APIs), or streaming platforms. Optimizes data processing and query performance by fine-tuning data pipelines, database configurations, and data partitioning strategies. Establishes data quality checks and validations to identify and resolve data issues, ensuring high-quality and reliable data for downstream applications and analytics. Implements security measures to protect sensitive data throughout the data lifecycle by working closely with security teams to ensure data encryption, access controls, and compliance with data protection regulations. Collaborates with cross-functional teams, including data scientists, analysts, software engineers, and business stakeholders. Designs and develops data infrastructure, including data warehouses, data lakes, and data pipelines. Establishes auditing and monitoring mechanisms to track data access and maintain data governance standards. Establishes monitoring and alerting mechanisms

Become a part of our caring community The Principal Storage Engineer is a senior technical leader responsible for defining and advancing the enterprise storage architecture and long-term data infrastructure strategy. This role establishes standards, develops five-year technology roadmaps, and designs secure, resilient, scalable, and cost-effective storage platforms for business-critical, analytics, and artificial intelligence workloads. The engineer serves as the organization’s storage subject-matter expert and partners with infrastructure, cloud, security, data, application, architecture, finance, and vendor teams to translate business requirements into sustainable technology capabilities. The Principal Storage Engineer is a senior technical leader responsible for defining and advancing the enterprise storage architecture and long-term data infrastructure strategy. This role establishes standards, develops five-year technology roadmaps, and designs secure, resilient, scalable, and cost-effective storage platforms for business-critical, analytics, and artificial intelligence workloads. The engineer serves as the organization’s storage subject-matter expert and partners with infrastructure, cloud, security, data, application, architecture, finance, and vendor teams to translate business requirements into sustainable technology capabilities. Key Responsibilities Define the enterprise storage vision, reference architecture, engineering standards, and five-year roadmap across block, file, object, software-defined, and hybrid storage services. Lead architecture decisions for on-premises AI infrastructure, including high-throughput and low-latency storage fo

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next-generation RISC-V and AI compute architectures. You will work across hardware and software teams to improve performance, programmability, and integration of our custom toolchains into real applications. This role is fully hands-on and central to how developers interact with Tenstorrent hardware across both traditional compute and advanced machine learning workloads. This role is Hybrid, based out of Santa Clara, CA, Austin, TX, or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced compiler engineer with deep knowledge of GCC and LLVM internals, comfortable optimizing for custom hardware targets. Strong C/C++ developer with a solid grasp of algorithms, data structures, and performance analysis. Collaborative and analytical, able to work across hardware and software domains to deliver efficient, high-performance toolchains. Passionate about enabling breakthrough compute architectures through compiler innovation and software-hardware co-design. What We Need Design, develop, and optimize GCC and/or LLVM compilers for Tenstorrent’s cust

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As a Staff DevSecOps Engineer in the ET team, you will be the technical authority and architectural owner responsible for embedding security, compliance, and automated release practices across our enterprise applications ecosystem—including Salesforce, NetSuite, Workday, Adobe Experience Manager (AEM), and modern web stacks (Vercel/Next.js) . In this role, you will bridge development, security, and enterprise ops. You will design, scale, and maintain automated security pipelines, unified observability, edge defense, and identity management across critical business systems. You will serve as a technical leader—driving secure-by-design architectures, threat modeling, and automated governance across complex enterprise platforms. Key Responsibilities: Enterprise DevSecOps Architecture & CI/CD Security Multi-Platform CI/CD Governance: Architect and scale enterprise-grade CI/CD and deployment frameworks across diverse systems (Salesforce via Gearset/Copado , AEM/Web via CircleCI/GitHub Actions , NetSuite, and Workday). Shift-Left Security Pipeline: Integrate automated SAST, DAST, Software Composition Analysis (SCA), and secrets detection into workflows using tools like SonarQube, Snyk, PMD, GitGuardian, and OWASP ZAP . Secrets & Supply Chain Management: Standardize secrets management (e.g., HashiCorp Vault ) and safeguard third-party dependencies, API integrations, and package deployments across all enterprise platforms. Edge, WAF & Network Security G

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 Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

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 Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. About the team and the role The Developer Tooling team builds internal tools and platforms that improve the velocity and developer experience of Cloudflare's engineering teams. We own developer productivity (code commit to production), developer insights and ADLC metrics, developer infrastructure (CI/CD, build systems), AI-assisted development, and Cloudflare-on-Cloudflare dogfooding. This team is responsible for AI-assisted development across all

MongoDB is expanding our global team of consulting engineers to further our ongoing plans for worldwide growth! MongoDB Professional Services works with customers of all shapes and sizes in all verticals, from tier-1 banks to small web startups, on a variety of interesting use cases from e-commerce platforms to trading systems to social media applications. Solve interesting problems, gain incredible cross-stack experience, work with the best and brightest people in the business, network with industry leaders, and see new places - all in a day’s work! MongoDB consulting exists to support the development of our customers’ vision, accelerate customers’ time to value, and drive a multitude of customer adoption scenarios - from building new solutions to modernizing legacy applications or migrating to the cloud. Our consulting solutions ensure that organizations get the best out of MongoDB. Be one of the recognized experts in this rapidly growing field in a high-growth software company successfully challenging the status quo of the database industry. You will have abundant opportunities to meaningfully impact the growth of our business in your region. We are looking to speak to candidates who are based in Tel Aviv for our hybrid working model. Candidate Profile We’re looking for a highly technical individual, with strong problem-solving and communication skills, and comfortable working closely with customers. Our ideal candidate will have Excellent analytical, diagnostic skills, and problem-solving skills High motivation for a role that combines deep technical and customer-management dimensions Confidence speaking and presenting in a collaborative customer setting 2+ years of software development/consulting/support experience, preferably in several distinct industries/verticals Familiarity with enterprise-scale software architectures, application development methodologies, and software deployment and operations Competence in at least one of the following languages (in no

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

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 We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain