Senior Detection And Response Engineer in India

Principal Product Manager - Agentic Investigation & Reliability Experiences Sumo Logic is hiring a Principal Product Manager to lead how engineers and operators investigate incidents, understand reliability risk, and act on their operational and security telemetry. The observability category was built around collecting telemetry and giving people tools to navigate it: dashboards, queries, monitors, traces, and alerts. Customer expectations are now shifting. Teams don't just want more dashboards; they want help getting from a signal to a resolution, understanding what's broken, why, what's impacted, and what to do next. As AI agents move into production operations, this role owns how Sumo Logic brings intelligent, agent-assisted investigation and reliability workflows to customers, grounded in evidence, context, and enterprise governance. This is a senior, high-ownership role. It requires genuine observability domain background. You should have lived in this space and understand how monitoring, troubleshooting, and reliability actually work, combined with the ambition to define a new category of experience on top of it. What You Will Own The current data experiences. Log Search, Live Tail, query and query optimization, Metrics Search, Tracing, Dashboards, and the data-experience UI. This is a live, revenue-generating product with real customers, and keeping it strong is part of the job. You own its health, roadmap, and competitiveness today while steering it toward an AI-native future, focusing new investment where it strengthens investigation, speed, and value for both new and power users. The reliability and alerting surface. Monitors, Alerts, SLOs, Scheduled Searches, and the reliability workflows around them. You will own alerting accuracy, noise reduction, and operational health signals both as capabilities customers depend on today and as the foundation for more automated, agent-assisted detection and investigation. The agentic investigation experience. You

Principal Product Manager - Agentic Investigation & Reliability Experiences Sumo Logic is hiring a Principal Product Manager to lead how engineers and operators investigate incidents, understand reliability risk, and act on their operational and security telemetry. The observability category was built around collecting telemetry and giving people tools to navigate it: dashboards, queries, monitors, traces, and alerts. Customer expectations are now shifting. Teams don't just want more dashboards; they want help getting from a signal to a resolution, understanding what's broken, why, what's impacted, and what to do next. As AI agents move into production operations, this role owns how Sumo Logic brings intelligent, agent-assisted investigation and reliability workflows to customers, grounded in evidence, context, and enterprise governance. This is a senior, high-ownership role. It requires genuine observability domain background. You should have lived in this space and understand how monitoring, troubleshooting, and reliability actually work, combined with the ambition to define a new category of experience on top of it. What You Will Own The current data experiences. Log Search, Live Tail, query and query optimization, Metrics Search, Tracing, Dashboards, and the data-experience UI. This is a live, revenue-generating product with real customers, and keeping it strong is part of the job. You own its health, roadmap, and competitiveness today while steering it toward an AI-native future, focusing new investment where it strengthens investigation, speed, and value for both new and power users. The reliability and alerting surface. Monitors, Alerts, SLOs, Scheduled Searches, and the reliability workflows around them. You will own alerting accuracy, noise reduction, and operational health signals both as capabilities customers depend on today and as the foundation for more automated, agent-assisted detection and investigation. The agentic investigation experience. You

SPECIFIC JOB RESPONSIBILITIES Pipeline Management: Maintain high-throughput streaming pipelines to ingest logs from various sources (Firewalls, Cloud, Endpoints) to a central destination. Log Normalization: Write parsers to convert raw, messy logs into standard schemas (e.g., OCSF or ECS) for consistent querying. Cost Optimization: Implement routing logic to send "high-value" data to the SIEM and "bulk" data to low-cost Object Storage (Data Lake). Data Preparation: Clean and structure data to enable AI/ML detection models and advanced analytics. EXPERIENCE REQUIRED Data Engineering: Proficiency in Python (for ETL) and SQL (for complex querying). Streaming Tech: Experience with Message Queues (e.g., Kafka, Pub/Sub) and stream processing concepts. Log Handling: Mastery of Regex and log parsing strategies for standard formats (Syslog, CEF, JSON). Storage Architecture: Understanding of Data Lake principles (Parquet/Avro formats) vs. Data Warehouses. QUALIFICATIONS, SKILLS, & KNOWLEDGE Experience with Vector Databases for storing embeddings. Knowledge of Log Observability/Routing tools (middleware that routes logs). Familiarity with Big Data frameworks (e.g., Spark, Flink). PROFESSIONAL DEVELOPMENT EXPECTATIONS Ability to embrace Clearwater's CLEAR core values (Commitment to Client Success, Lead with Accountability, Integrity & Collaboration, Excellence in All That We Do, Advance Colleague Success, Respect & Transparency) and culture. The base salary range for this role is 35,000- 45,000]. Base salary is part of our total rewards package which also includes the opportunity for merit-based salary increases, eligibility for our 401(k) plan, medical, dental, vision, life and disability insurances and leaves provided in line with your work state. Our robust time-off policy includes flexible paid time off, 11 paid holidays, and paid sick time. Total compensation, including base salary to be offered, will depend on elem

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Senior Security Operations Engineer – Attack Surface Management , you will help engineer, operate, and continuously improve our enterprise Attack Surface and Vulnerability Management capabilities. You will focus on discovering and understanding our attack surface, identifying vulnerabilities and exposures, prioritizing them based on real-world risk, and driving remediation across our global environment. The role spans Attack Surface Management, Vulnerability Management, Zero Trust, Secrets and Credential Security, SSPM, Deception, Detection Engineering and Security Automation. We are looking for engineers with strong ASM/Vulnerability Management fundamentals and deeper expertise in one or more adjacent security domains. WHAT YOU’LL DO Engineer and improve enterprise Attack Surface and Vulnerability Management across cloud, infrastructure, endpoints, applications, and internet-facing environments. Discover and correlate assets across security platforms and identify unknown, unmanaged, stale, and externally exposed assets. Drive risk-based vulnerability prioritization using asset criticality, exposure, exploitability, known exploitation, threat intelligence, and compensating controls. Establish remediation workflows and SLAs and partner with asset owners to drive measurable risk reduction. Operate and troubleshoot Zscaler ZIA/ZPA, including SSL inspection, access policies, connectivity, and Zero Trust controls.

About Paytm: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. We offer competitive compensation, opportunities for professional growth, and a dynamic work environment. About the Team: The Compliance department has five areas of responsibility—identification, monitoring, advisory, reporting and review for the entity with respect to regulations/ laws. About the role: This role includes managing regulatory compliance for UPI TPAP, BBPS and Digital Lending Business. The role entails advising the UPI TPAP, BBPS, Digital Lending business units of the relevant regulatory expectations and ensuring timely monitoring and detection of compliance-related issues. The successful candidate will be responsible for individually contributing and ensuring compliance with relevant laws, regulations, and guidelines related primarily to UPI TPAP, BBPS and Digital Lending. The ideal candidate should have experience in relevant domain dealing with RBI and NPCI obligations preferably in a fintech environment, bank and possess strong self-driven skills to manage compliance effectively. Expectations/ Requirements: 1) Regulatory Compliance Management and Monitoring: Monitoring and interpreting regulations and guidelines in the domain of UPI TPAP, BBPS and Digital Lending and ensuring compliance with applicable laws, regulations, and guidelines. Provide informed compliance advisory to the internal stakeholders on the applicability of regulatory laws and guidelines. 2) Policy and Procedure Development: Develop, implement, and maintain compliance policies and procedures ensuring that they are up-to-date. 3) Regulatory Reporting: Prepare and submit timely and accurate compliance reports to senior ma

Screener is responsible to ensure the safe and efficient screening of hold baggage, ensuring compliance with regulatory standards and the detection of prohibited items or security threats. The Screener will be responsible for operating screening equipment, documenting findings, collaborating with other security staff, and interacting with passengers to maintain the highest standards of security. Source: Adani Group | Job ID: 49118

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. The Role You'll be our dedicated expert in query execution and query performance. That means owning the query execution service end-to-end: working on caching strategies, incremental execution, query rewrites, and other optimizations that directly affect the speed and cost of running Observe at scale. You'll also be the go-to resource when query latency issues arise during customer evaluations and new deal cycles, diagnosing root causes

Role Overview You are a senior product leader who wants to shape how AI transforms IT and cyber risk management at scale. In this role, you will own one of the most strategic product areas in a global GRC SaaS platform, defining how organisations identify, assess, and act on cyber risk — and how CISOs and boards get the clarity they need when it matters most. You will set and drive the product vision, roadmap, and outcomes for IT & Cyber Risk on a multi-solution platform used by enterprises worldwide. You will partner closely with engineering, design, data science, and senior leaders to build AI-native capabilities that automate risk detection, prioritisation, and reporting. Your work will have high executive visibility, real strategic weight, and direct impact on how customers manage governance, risk, and compliance. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the end-to-end product strategy and roadmap for IT & Cyber Risk, aligning to company objectives and broader platform direction. Design and deliver AI-powered features (LLMs, agents, ML models) that automate risk identification, assessment, and reporting for enterprise security and risk teams. Partner with engineering, data science, and design to define technical approaches, ship high-quality releases across web, mobile, and API, and iterate using product analytics. Develop deep market and customer insight by engaging regularly with CISOs, security leaders, and risk managers, and turn those insights into clear product bets. Define, track, and communicate product KPIs, AI performance metrics, and north star outcomes to senior stakeholders, including business cases for major investments. Work cross-functionally with Sales, Customer Success, Professional Services, and Marketing to ensure successful launches and adoption of new IT & Cyber Risk capabilities. These are the essentials you’ll need to get an interview 7+ years of product management experience, includi

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! We are the Silicon Power Team within the Silicon Co-Design Group. We architect and deliver groundbreaking solutions for productizing NVIDIA's chips across consumer, professional, server, embedded, mobile, and automotive markets. Silicon characterization, correlation to arch and design expectations, product spec finalization, and productization techniques and infrastructure are our day-to-day work — always on the bleeding edge of the industry. Small decisions here have outsized impact on performance, efficiency, reliability, bring-up speed, and ultimately what the product delivers in the field. We are hiring a Senior Silicon Power Engineer to own power-feature productization on a flagship silicon program. This is not a coordination role, and it is not a compliance role — it is the seat where power features either work at scale or become the reason a program slips. The two highest-leverage problems in this seat: Close the hardest multi-functional power failures before they gate a program. Take ambiguous, cross-boundary issues across architecture, firmware, validation, and platform to root-cause closure — with productized fixes and reusable methodology the next program can inherit. Build AI-enabled characterization as a real capability, not a demo. Every bring-up generates terabytes of characterization, shmoo, and telemetry data. Deploy AI workflows for data analysis, metric extraction, trend detection, and cross-bring-up correlation — with the guardrails and validation discipline to make them trustworthy enough to gate production decisions! <

We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineerin

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. We are hiring a Senior Frontend Engineer, AI Products team at Observe by Snowflake. As an AI Product engineer you'll always be thinking first about the user experience and how to create the best product, technical choices, and implementation decisions that stem from that product first thinking. This team builds the AI-powered products and developer tooling at the core of Observe's platform, including our flagship AI SRE product, real-tim

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. The Role You will work on our Metrics platform - enabling our users to query, visualize, and alert on billions of time series quickly and effectively. You'll own meaningful parts of that stack, drive performance and scalability improvements, and contribute to architectural decisions that shape where the platform goes next. This isn't a maintenance role, the metrics backend is being actively evolved, and you'll be a core part of that. Thi

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper