Senior Software Engineer Java 26 Python in India

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. Senior Backend Engineer - Platform Insights An overview of this role As a Senior Backend Engineer in Platform Insights, you'll build and evolve the core backend systems that power GitLab's data platform. In this role, you'll focus primarily on Go-based development for the Data Insights Platform and Siphon, with an emphasis on core system design, production readiness, and deployment across GitLab environments. You'll own high-throughput, multi-component backend systems and help shape architecture, reliability, deployment, and operational maturity across GitLab's SaaS, Dedicated, and Self-Managed environments. What you'll do Design

Location Details: Pune, India At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team. Join our Team Our team builds and operates the foundational infrastructure platforms that power GoDaddy's engineering organization. We own critical services including secrets management, software distribution, host security controls, and live patching for thousands of Linux systems running on OpenStack. This role sits at the intersection of Linux engineering, platform engineering, reliability engineering, and security. You will help define how core infrastructure services are designed, operated, automated, and scaled across the enterprise! What you'll get to do... Design, build, and operate highly available, scalable, and secure infrastructure platforms supporting large-scale Linux environments, with a focus on reliability, resiliency, and operational efficiency Lead the architecture, implementation, and operation of infrastructure services, including OpenStack, enterprise secrets management, package management, software promotion pipelines, and platform lifecycle management Develop and maintain automation solutions using infrastructure-as-code, Ansible, Python, Go, and self-service capabilities to improve efficiency and reduce operational overhead Build and improve observability and reliability practices through monitoring, logging, alerting, dashboards, managing incidents, analyzing underlying causes, disaster recovery, and service health reporting

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

Senior -Power and Performance Validation Engineer About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to deb

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software, and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers, and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Validation leadership team, the Senior Execution and Quality Validation Engineer will be responsible for executing validation plans, developing automation solutions, and improving product quality across Graphcore silicon and platform technologies. Working closely with architecture, design, verification, firmware, software, systems engineering, and validation teams, the successful candidate will contribute to scalable validation methodologies, improve test coverage and execution efficiency, and help ensure products meet high standards of functionality, reliability, and performance before customer deployment. The role requires strong technical skills, attention to detail, and a passion for improving validation quality through effective execution, automation, and continuous improvement. The Team The Validation Execution and Quality team sits within the Validation organisation and is responsible for improving validation effectiveness, test execution efficiency, product quality, and release readiness across Graphcore silicon and platform products. The team develops validation methodologies, automation

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

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! <

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

What We Do At GoGuardian, we’re helping build a future where all learners are ready and inspired to solve the world’s greatest challenges. Our award-winning system of learning solutions is purpose-built for K-12 and trusted by school leaders to promote effective teaching and equitable engagement while helping empower educators to keep students safe. What It’s Like to Work at GoGuardian We are an outcomes-focused learning company with a steadfast focus on improving learning environments, one classroom at a time. Working with us means joining a remote team of diverse, committed, mission-driven employees who are inspired by our vision, dedicated to our customers, and ready to roll up their sleeves. Guardians put their heads together to solve problems, learn together from experiments that fail, and stand together by their work with full accountability. We balance our diligence with an inclusive culture that invites everyone to bring their whole self to work. Join us and learn why “I love the people here” is one of the most frequent comments we hear from Guardians. What We Do At GoGuardian, we’re helping build a future where all learners are ready and inspired to solve the world’s greatest challenges. Our award-winning system of learning solutions is purpose-built for K-12 and trusted by school leaders to promote effective teaching and equitable engagement while helping empower educators to keep students safe. The Role We’re looking for a Senior Site Reliability Engineer (SRE) to help design, scale, and maintain the infrastructure that powers our core products and services. In this role, you’ll collaborate with engineering teams to drive operational excellence, optimize system performance, and ensure high availability across production environments. This position sits on Tech Foundation, a team that manages core cloud infrastructure, shared data services, and developer tooling to empower our product teams to deliver software efficiently and secu

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

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

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

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

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

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