Senior Detection Engineer in India

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.

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 hands-on senior leader for our India SecOps team, you will shape and safeguard Everpure’s security posture at the intersection of detection engineering, threat hunting, attack surface management, and incident response. Positioned as a strategic cornerstone in Bangalore, you will empower an elite engineering team, optimize critical SecOps pipelines, and partner cross-functionally across global engineering and infrastructure groups. By driving execution excellence and high team morale, you ensure our enterprise platform and global telemetry remain resilient against evolving threats. WHAT YOU'LL DO Scale & Lead SecOps Operations: Architect, mentor, and grow the India SecOps team to foster an environment of high morale, technical excellence, and rapid execution across detection engineering and incident response. Proactively Manage & Remediate Attack Surface: Own end-to-end Attack Surface Management (ASM) across cloud environments, SaaS applications, endpoints, and secrets management to measurably minimize enterprise exposure and mitigate risk. Optimize Telemetry & Incident Response: Mature SIEM and SOAR automation pipelines to drastically reduce mean time to detect, contain, and respond (MTTD/MTTC/MTTR) while continuously elevating alert fidelity and signal confidence. Drive Cross-Functional Alignment & RCA Postmortems: Lead continuous validation through purple-teaming and incident postmortems alo

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. Technical Architect: Company Description Okta is the leading independent identity partner. We enable organizations to securely connect the right people and technologies, providing identity solutions that protect workforce and customer identities across a rapidly evolving technology landscape. The P0 Threat Research organization operates at the intersection of adversary research, threat hunting, detection engineering, data science, and product innovation. Our mission is to understand modern adversaries better than anyone else and make that knowledge actionable for our customers and products. Position Description Architect, Threat Research will help define and drive the technical vision for Okta's threat research efforts. This role is focused on understanding how modern adversaries operate, developing new methodologies for discovering and analyzing attacker behavior, and translating that research into actionable outcomes for our customers and products. Initial areas of emphasis include identity, cloud, SaaS, AI, and other emerging technologies, but success in this role is rooted in deep threat research expertise and the ability to rapidly develop expertise in new technologies and attack surfaces. The Architect will serve as a senior technical leader within the Threat Research organization. This individual will work closely with threat researchers, threat hunters, detection engineers, data scientists, product teams, engineering teams, and other senior t

We are fueled by a moral imperative to advance mankind, and it all begins with our people, our product, and our purpose. Passion isn’t something we turn on and off; it’s woven into everything we do. If you thrive in high-challenge environments, are inspired by exceptional teammates, and are driven to grow beyond what you thought possible, MX is where you belong. Come build the future with us. Join an award-winning company that isn’t just shaping the financial industry, but transforming it in ways that create meaningful, lasting impact for millions of people. At MX, reliability is a product. Our infrastructure powers financial applications used by millions of people and processes billions of transactions for major financial institutions, and customers feel every second of downtime. We're building a new observability function that runs the way we run incident response: the system does the heavy lifting, and people handle judgment, customers, and the exceptions. As a Senior Observability Engineer, you build and operate an observability control plane. You scaffold baselines, score coverage, and turn every real incident into the detection the platform should have caught. This is a multiplier role: you raise the bar for every team through standards and automation instead of building each team's dashboards by hand. We call it the shepherd model. You shepherd Datadog and partner with our product engineering teams so they observe the right signals for their products. Service owners get real signal instead of noise, and leadership gets coverage and health as a program metric. This role shares the team pager. Observability and incident response run one on-call roster. You take shifts with the rest of the team and act as Incident Commander when an incident needs one. It is core to the role, not an afterthought. Engineering at MX runs hybrid infrastructure (AWS and bare metal) with services in Ruby, Go, and Java, messaging over NATS and RabbitMQ, and data on PostgreSQL an

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

Overview: The role is responsible for managing and supporting the operations of Global Network Engineering in a hybrid/cloud environment and provides senior-level expertise to the network engineering team. We're looking for an expert in on-premises networking, cloud infrastructure networking (Azure/AWS), and telecommunications (VOIP) in global environments, with knowledge and focus on zero-trust networking methodologies. This position requires off-hours on-call availability. This is a remote position with a 3 PM - 12 AM Shift. Candidates may need to visit the Mumbai office as and when needed in the general shift. What You'll Do: Manage physical network management and support covering Guidepoint offices, including, but not limited to, firewalls, routers, switches, etc. Responsible for managing the Enterprise WiFi Operations ZScaler Network management Monitor global traffic latency, issues, and application performance Update and design next-generation network models Network detection and response Intrusion detection and prevention technologies Azure Cloud Traffic integrating with On-prem traffic Azure Web Security CASB models and methodologies What You Have: 8+ years of experience with core networking in an enterprise environment, ideally global network design and security methodologies. 5+ years of working experience with advanced Azure cloud networking technologies. Must have substantial experience with managing WiFi Operations. CCNP Certified or equivalent experience 3+ years of hands-on experience, preferably with Sonic-wall/Netgear. Solid engineering knowledge of routing, switching (VLANs), Azure networking, firewalls, and traffic management. Update network security based on VNETs and Subnets, with traffic monitoring, etc. Knowledgeable in Azure Application Gateways, Front Door, and other security tools. Nice to have: Must know telecommunication technologies (VOIP, SIP Trunking, Microsoft Teams) Network security experience (vulnerability manage

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

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

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! <

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

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

Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Backend Engineer at GitLab, you will help shape a major investment in our Software Supply Chain Security offering. In this role, you'll serve as a senior technical leader for backend systems that help customers secure how software is built, verified, and delivered inside the GitLab platform. You'll work on foundational capabilities across package policy enforcement, build provenance, artifact signing, and malicious package detection, with a strong focus on enterprise-grade security and performance. You'll define architecture before systems are built, write clear technical proposals, and guide i

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