Performance And Systems Engineer in India

Couchbase, the operational data platform for AI, empowers businesses to succeed by bringing data to life in new ways. Major market-leading companies rely on Couchbase for mission critical operational, analytical, mobile and AI workloads. Built to replace legacy infrastructure and fragmented data services, Couchbase empowers enterprises with a unified platform architected for performance, flexibility and global scale. With Couchbase, organizations bring their data to life, launching game‑changing customer experiences, exploring the limitless potential of AI, and seamlessly extending applications from the cloud to the edge and beyond. Couchbase’s AI‑ready technology and enterprise partnership model eliminate complexity and reduce total cost of ownership, enabling teams to stay agile, innovative and secure. Couchbase believes data should never slow you down, but act as the foundation for your next breakthrough. Discover why Couchbase is trusted to help the world’s biggest players scale, move fast and stay resilient, no matter what’s next on their roadmap. Visit couchbase.com and follow us on LinkedIn and X. Want to be part of our story? Apply today! AI Platform Engineering Location: Bangalore (Hybrid - in office at least 3 days/week) About the Role We are seeking an experienced and visionary technology leader to lead the development and scaling of our Operational AI platform capabilities. This role will own the strategy, architecture, delivery, and operational excellence of Couchbase AI Cloud Platform capabilities. This is a strategic leadership role at the intersection of distributed systems, cloud-native platforms, and AI. You will lead a large, multi-layered engineering organization responsible for delivering The Operational Data Platform for AI, while partnering closely with Product, Design, SRE, and Go-To-Market teams. Your leadership will directly influence company growth, customer adoption, platform reliability, and Couchbase’s competitive pos

WE'RE HIRING Senior SQL Data Engineer Azure & Snowflake Remote (WFH) Immediate Joiners only Location: Remote Employment Type: Full-Time Immediate Joiners Preferred Salary: Up to 8 LPA (PF Included) Experience: 4+ Years We are looking for a highly skilled Senior SQL Developer with strong experience in Microsoft Azure and Snowflake to design, develop and optimize enterprise data solutions. Must have 4+ years as a SQL Developer, Data Engineer, or Data Warehouse Developer, The successful candidate will have excellent SQL development skills, a strong understanding of data warehousing and data modelling, and hands-on experience building cloud-based data pipelines and analytical platforms. The role involves working closely with data architects, engineers, analysts and business stakeholders to deliver reliable, scalable and high-performing data solutions. Key Responsibilities -Design, develop and maintain complex SQL queries, stored procedures, views, functions and database objects. -Must have 4+ years as a SQL Developer, Data Engineer, or Data Warehouse Developer -Build and optimise data transformation processes for large-scale datasets. Develop data pipelines using Azure Data Factory, Azure Synapse Analytics and related Azure services. -Design and implement data solutions within Snowflake. -Develop Snowflake tables, views, stored procedures, streams, tasks, stages and file formats. -Create and maintain ETL and ELT workflows across Azure, Snowflake and source systems. -Analyse and improve the performance of SQL queries, data pipelines and warehouse workloads. Design dimensional models, including star and snowflake schemas, fact -tables and dimension tables. Implement data quality checks, validation rules, reconciliation processes and error-handling frameworks. -Support data migration and modernisation programmes from on-premises platforms to Azure and Snowflake. -Develop incremental loading, Change Data Capture and Slowly Changing Dimension solutions. -Troubleshoot da

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

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 manages observability, monitoring, and detection for systems that support customer purchasing and use of GitLab. As a Staff Backend Engineer on the Fulfillment Workflow Monitoring (Catch All) team, you'll set the technical direction for the telemetry, detection, and reconciliation tooling that identifies billing, data, and event anomalies across CustomersDot, Salesforce, and Zuora before they can affect revenue or the customer experience. This is a greenfield team. You'll help build it from the ground up, shaping its operating rhythm, incident response

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. Okta’s Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate software security engineer to join a team focused on designing and developing Security solutions to harden our frameworks & infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security software solutions that help run large-scale, mission-critical software. We encourage you to prescribe defense-in-depth measures, industry security standards, enforce the principle of least privilege to help take our Security posture to the next level. Our Security engineering team has a niche skill-set that combines Security domain expertise with the ability to design, implement and rollout security features and functionalities without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the engineering org to build technical leverage and influence the security roadmap and direction. You will focus on engineering security and privacy aspects of the systems used across our services while working on a weekly release cadence. You will be empowered to propose stimulating new

About the Role At Jumio, the Software Development Engineer IV - QA (SDE-IV, QA) is a senior technical role focused on ensuring the quality, performance, and reliability of highly scalable web portals and distributed backend systems. Our platform spans multiple Java Spring Boot microservices and customer-facing web portals , deployed across AWS ECS, EKS, and Lambda , and integrated through event-driven messaging using SNS/SQS . In this role you will design and drive the test automation strategy for both UI (Playwright) and API/service layers, set the quality bar for the team, and act as a force multiplier — mentoring other engineers and embedding quality earlier in the development lifecycle. You will work closely with development, product, and DevOps teams to ensure our products meet the highest standards of quality, scalability, and security. This is a hands-on senior IC role: you will write code, but you will also influence architecture, own cross-service test strategy, and make build-vs-buy decisions for testing tooling. T-Shaped Engineering Expectation As part of Jumio's engineering culture, you will adopt a T-shaped engineering approach. Beyond deep expertise in test automation and quality engineering, you will contribute across the development lifecycle — understanding software architecture, participating in design and API-contract discussions, reviewing application code, and ensuring our distributed systems are testable, observable, and resilient by design. Role Value This role is critical to ensuring the reliability, scalability, and security of Jumio's products. By architecting and maintaining automated testing frameworks across web, API, and event-driven layers, you will enable faster, higher-confidence releases and reduce production risk in a complex microservices environment. What You'll Do Test Architecture & Strategy Define and own the end-to-end automated test strategy across web portals and backend microservices, balancing UI, API, contract, integ

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

The Lead EMS/SCADA will be responsible for the design, development, integration, testing, and deployment of Energy Management Systems (EMS) and SCADA solutions for utility-scale Battery Energy Storage System (BESS) projects. The role will drive system architecture, control strategies, monitoring solutions, and communication interfaces to ensure optimal performance, reliability, and grid compliance. Source: Adani Group | Job ID: 58677

100% Remote | Senior Frontend Engineer | Fintech SaaS Firm About the Role We’re looking for a Senior Frontend Engineer to build and maintain scalable, high-performance user interfaces for our communication platform. You’ll work closely with backend engineers, designers, and product managers to deliver exceptional user experiences while keeping performance, maintainability, and scalability at the core. What You’ll Do Develop and maintain responsive UIs using React JS, TypeScript, JavaScript, HTML5, and CSS. Collaborate with cross-functional teams to design and deliver high-quality features. Write clean, maintainable, and well-documented code. Optimize performance with caching and other best practices. Review code, mentor peers, and uphold coding standards. Debug and troubleshoot production issues promptly. Stay current with frontend trends and bring innovative ideas to the team. Job qualifications: 3–8 years’ experience in web development with a focus on scalability. Expert in React JS, JavaScript, TypeScript, HTML5, and CSS. Strong grasp of responsive design, performance optimization, and client-side session management. Familiarity with Git, CI/CD, and distributed development. Excellent problem-solving and collaboration skills. Preferred/Bonus Skills Experience with React Native or other mobile development frameworks. Familiarity with state management libraries like Redux or Zustand. Experience with modern build tools such as Webpack or Vite. A strong portfolio or active GitHub profile showcasing previous work. Why Join Eltropy? Join a high-impact team building mission-critical backend systems for financial institutions. Work on modern technology stacks in a fast-growing SaaS company. 100% remote work with a collaborative, engineering-led culture. Opportunity to own and influence core backend architecture. About Eltropy Eltropy is a rocket ship FinTech on a mission to disrupt the way people acc

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge We're looking for a Staff Software Engineer to lead technical direction across a major feature area or system domain at OneTrust. Staff Engineers here own outcomes, not just designs; they decide how ambiguous, cross-cutting problems get solved when no existing playbook applies, and their judgment carries weight across teams they don't formally manage. Your Mission Technical Leadership & Architecture Lead architecture and design for systems with significant scope and blast radius, ensuring decisions hold up under real growth, compliance, and reliability constraints; not just initial requirements. Paying attention to application performance Exercise judgment on where AI-assisted tooling accelerates delivery and where deeper human design thinking is required Cross-Team Collaboration Partner with Product, UX, and other engineering teams early, shaping problems before solutions are locked in. Build working relationships and technical credibility beyond your immediate team. Quality & Standards Set engineering practices for code revie

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge We're looking for a Staff Software Engineer to lead technical direction across a major feature area or system domain at OneTrust. Staff Engineers here own outcomes, not just designs; they decide how ambiguous, cross-cutting problems get solved when no existing playbook applies, and their judgment carries weight across teams they don't formally manage. Your Mission Technical Leadership & Architecture Lead architecture and design for systems with significant scope and blast radius, ensuring decisions hold up under real growth, compliance, and reliability constraints; not just initial requirements. Paying attention to application performance Exercise judgment on where AI-assisted tooling accelerates delivery and where deeper human design thinking is required Cross-Team Collaboration Partner with Product, UX, and other engineering teams early, shaping problems before solutions are locked in. Build working relationships and technical credibility beyond your immediate team. Quality & Standards Set engineering practices for code revie

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and