Software Engineer L2 Cloud Infrastructure Salary Guide in Bengaluru

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 The Observability, Monitoring, and Integrations team sits within GitLab's Monetization section. As a Senior Backend Engineer on the Monetization Platform Integrations team, you'll design, build, and maintain the integrations that connect CustomersDot and Monetization services to GitLab's enterprise applications, including Salesforce and Workato. You'll own robust application programming interface (API) contracts, protect data integrity across systems, and build resilient cross-platform workflows that underpin how customers buy, provision, and renew GitLab. Because these integrations move financial and sub

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. As a Staff Site Reliability Engineer (SRE) at GitLab, you’ll help keep all user-facing services and production systems reliable, scalable, and efficient. Our SREs combine a pragmatic operations mindset with strong software engineering practices to drive automation, reduce toil, and improve resilience across our platform. In the Environment Automation specialization, your focus is on operating and automating hundreds of GitLab environments—from initial provisioning to day-to-day maintenance tasks. Unlike other SRE roles, this position centers on automating the lifecycle of many tenant environments, ensuring they remain secur

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As a Senior Data Engineer , you will own the data foundation of Zinnov’s GCC Intelligence Platform—building reliable multi-tenant pipelines and KPI-ready datasets across Finance and Hiring domains. Your work enables downstream dashboards and AI agents to operate on clean, reconciled, governed data. What You’ll Do Data Pipelines & Medallion Architecture Build andmaintainingestion pipelines from source systems (e.g., Dynamics, Workday, Airtable, SFTP feeds). Design and implement Medallion pipelines (Bronze → Silver → Gold) across Finance and Hiring data. Build reconciliation and gating logic to ensure only validated data reaches Gold. Multi-tenant Data Modeling Design multi-tenant PostgreSQL schemas with row-level s

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As an Agent / AI Engineer , you will build the AI layer of the GCC Intelligence Platform—the conversational agent users interact with. You will own grounding, retrieval, persona routing, session state, and permission-aware querying so the agent stays accurate, secure, and tenant-safe. What You’ll Do LLM & Agent Integration Integrate LLM APIs (e.g., AzureOpenAIor equivalent) for conversational workflows. • Build a grounding layer that anchors responses to real platform data (not model guesses). • Maintain prompt templates across multiple personas and use-cases. Retrieval, Permissions & Security Boundaries Implement intent classification and persona routing to the right KPI views. • Build the API

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As a Full Stack Engineer , you will build the product experience—dashboards, chat interface, persona-specific layouts, and the API layer that connects UI to agent + data layers. You will also own internal workflows that enable finance sign-off and platform governance. What You’ll Do UI & Product Experience Build theNextJSweb app: dashboards, chat interface, and persona-based views. Implement data-heavy UI patterns: tables, drilldowns, charts, exports. Ensure accessibility, usability, and consistent experience across personas. Backend-for-Frontend (BFF) Build andmaintaina NestJS BFF layer connecting UI to agent/data services. Treat BFF APIs as versioned platform contracts—manage changes cleanly. A

Identity has become a critical to an organizations security posture. This is true across their entire digital landscape include cloud, traditional on prem and emerging technologies like agentic ai. Britive is at the forefront of a modern approach to delivering identity security with the only modern privileged access management platform that provides unified Privileged Access Visibility, Dynamic Privilege Management and Secrets Governance across infrastructure, platforms & SaaS. Our patent-pending technology is deployed at companies of all sizes around the world, including Fortune 500 companies. We have repeatedly ranked among the hottest Cloud Security startups. Britive is founded by CyberSecurity industry veterans with a successful prior exit and is backed by top-tier VCs. Key Responsibilities Ensuring Quality standards across various projects in Britive by adhering to quality engineering practices, testing and release planning for Quality Engineering team across releases. Performing manual testing and help maintain quality standards of software. Collaborate with QA team members, development, UI/UX engineers, and project managers to build a creative, powerful and unified user experience for our cloud access application. Analyze product requirements and develop test designs, including test strategy, test setups by identifying right test cases. Reviewing all product artifacts related to testing (e.g. plans, requirements, specifications, tests, test results, traceability, design reviews, reports, etc.). Involved in all quality engineering activities including working with Performance Testing Team and ensuring all the testing activities for the release are adhered too. Continually work on improving metrics gathering and bring up initiatives to improve the Quality Engineering team. What will you need? Required Skills: Prior experience working in a security software product comp

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

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’re looking for a hands-on RTL Design Engineer to own the microarchitecture and RTL implementation of the Power Management Subsystem/Interrupt Controllers/AXI Interconnect/Cache Controller . You’ll collaborate with cross-functional teams—architecture, firmware, software, DV, and PD—to define, design, and optimize power management solutions for next-generation RISC-V/ARM-based SoCs. This role is hybrid, based out of Bangalore, India. We welcome candidates at various experience levels. During the interview process, you will beevaluated and offered a level that aligns with your experience, which may differ from the one in this posting. Who You Are 5–10 years of experience in ASIC/SOC/IP design, with hands-on experience in microarchitecture and RTL development Skilled in Verilog/SystemVerilog and comfortable working across design, debug, and analysis Design and develop microarchitectures for a set of highly configurable IPs Microarchitecture and RTL coding ensuring optimal performance, power, area Work with verification teams on assertions, test plans, debug, coverage, etc. Deep understanding of power management concepts—clocking, reset, DVFS, and low-power modes Familiar with RISC-V or ARM-based SoCs and standard bus protocols (AXI, AHB, APB, CHI) Awareness of functional safety (ISO 26262) practices in hardware design What We Need Abil

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

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

Principal Embedded SW/FW Engineer (Bringup) - Bengaluru, multiple vacancies Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential:

Staff Embedded SW/FW Engineer (Bringup) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. 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. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team developing C code used to validate cutting-edge, high-performance AI chips and platforms. You will play a critical role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Bringup team, you will be involved with bringing first silicon to life, developing code primarily in C to configure and exercise systems and sub-systems on new silicon devices, and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to, and be responsible for, leading, mentoring, and providing technical guidance to other engineering team members. In this role, you can leverage your experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Respons

Job Summary Reporting to the Memory Validation leadership team, the Senior Silicon DDR/HBM Validation Engineer will be responsible for the bring-up, validation, characterization and debug of advanced memory subsystems used in next-generation AI compute platforms. The role will focus on DDR and HBM technologies, working closely with silicon design, firmware, characterization, platform and systems teams to ensure robust memory subsystem functionality, performance and reliability. The successful candidate will take ownership of significant validation activities, contribute to debug and root-cause analysis efforts, and help improve validation methodologies, automation and infrastructure. The Team The Memory Validation team sits within the Validation organisation and is responsible for the bring-up, validation, characterization and debug of memory subsystems across Graphcore silicon and platform products. The team supports DDR and HBM validation activities throughout the product lifecycle, from first silicon through production readiness. Engineers work closely with architecture, RTL, firmware, characterization, systems and platform teams to ensure memory technologies meet functionality, performance, reliability and performance objectives. Responsibilities and Duties Execute validation and bring-up activities for DDR and HBM memory subsystems Verify memory bring-up software, firmware and scripts against defined project requirements Debug firmware, hardware and system-level issues and contribute to root-cause analysis activities Analyse system logs, validation data and characterization results to identify failures and performance issues Perform PHY characterization and analog-level analysis during stress testing and validation activities Develop and execute functional, stress, performance and corner-case validation tests Perform signal integrity, voltage, frequency and timing measurements using laboratory instrumentation Char

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. The Engineering Opportunity We are looking for an experienced Senior Site Reliability Engineer to join Okta's Emerging Products Group (EPG). Our mission is to build highly reliable, scalable, and secure cloud services that our customers can trust. We embrace an automation-first mindset and continuously invest in platform engineering, observability, and operational excellence to enable our engineering teams to move quickly and safely. This role is ideal for an experienced Site Reliability Engineer who enjoys solving complex technical challenges at scale, building automation, and improving the reliability of production systems. You will serve as a key contributor within the EPG SRE organization, partnering closely with software engineers, architects, and product teams to design, build, and operate world-class cloud services. What You'll Be Doing Reliability & Operations Design, build, and operate large-scale cloud infrastructure and production services. Participate in an on-call rotation supporting highly available customer-facing systems. Lead incident response efforts and drive post-incident reviews focused on systemic improvements. Define, measure, and improve Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets. Partner with engineering teams to improve service availability, scalability, performance, and resilience. Continuously improve observability through metrics, logging, tracing, dashboards, and alerting. Eng