Systems And Solutions Engineer in India

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

Who we are Graviton Research Capital is a privately funded quantitative trading firm. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Role Overview We are looking for a Program Manager who thrives at the intersection of rigorous engineering and predictable delivery. You will not just "manage tasks" — you will orchestrate the development lifecycle for mission-critical systems. Your goal is to ensure that our elite engineering teams can focus on high-performance code while you own the execution strategy, dependency mapping, and release discipline. Key Responsibilities Lead Agile ceremonies (Sprint Planning, Stand-ups, Retrospectives) tailored for deep-tech engineering teams. Transform high-level trading requirements into granular, executable backlogs. Own capacity planning and burn-down metrics to provide high-visibility delivery timelines. Navigate the complex interplay between engineering teams (e.g., Connectivity, Core Infrastructure, Simulation) to prevent bottlenecks. Build and maintain advanced Jira dashboards, automated roadmaps, and Confluence documentation that serve as the "single source of truth" for stakeholders. Proactively identify technical debt, architectural blockers, or resource gaps that threaten release stability. Continuously refine Agile methodologies to suit low-latency, performance-sensitive development cycles (where "Definition of Done" includes rigorous performance benchmarking). Eligibility & Required Skills 5+ years of experience as a TPM, Program Manager, or Scrum Lead in a product-engineering environment (HFT, FinTech, Networking, or Kernels/Systems). A strong grasp of the software development lifecycle for high-performance systems. While you won't write code, you must understand concepts li

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

Research Engineer, Applied AI Location: Bangalore (or throughout India remote-friendly with travel) About EnCharge AI: EnCharge AI is building the next generation AI platform. Our novel in-memory-computing architecture delivers a 10x step-function improvement in compute energy efficiency and performance for AI inference workloads. As the demands of artificial intelligence move beyond today's models, we believe fundamental underlying infrastructure must evolve. We are an experienced team of AI researchers, silicon & systems engineers, and architects backed by leading investors, poised to become the essential platform for the next wave of AI innovation. The Opportunity: Modern AI workloads—from large language models to diffusion-based generators to multimodal systems—represent some of the most compute-intensive frontiers in AI, and some of the most promising applications for our hardware’s energy efficiency advantages. We’re building a vertically integrated AI stack that will showcase the transformative potential of our silicon while delivering real value to customers today. We are seeking a Research Engineer to push the boundaries of AI model capability, quality, and efficiency. You’ll build fine-tuning and post training pipelines, develop rigorous benchmarking frameworks, and work at the intersection of ML research and hardware-aware optimization—ensuring our models run beautifully on our silicon. This is a role for someone who thrives at the boundary between research and engineering. You’ll read papers, implement techniques, and ship production-quality code—all in service of making AI inference faster, cheaper, and better. Key Responsibilities: Algorithmic Acceleration: Research and implement state-of-the-art techniques to accelerate AI inference—quantization, sparsity,

Location Details: India, Remote 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 remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team... Here at GoDaddy, the ML Engineering (MLE) team exists as the backbone of our machine learning infrastructure, enabling ML scientists and product teams across Domains to ship models to production reliably, efficiently, and at scale. This team owns the full lifecycle of ML systems — from CI/CD pipelines and model serving infrastructure to GPU workload orchestration and observability. Through disciplined engineering practices, thoughtful system design, and close collaboration with ML scientists, data engineers, and product teams, we deliver the platform that powers domain search, pricing, recommendations, and emerging AI experiences for millions of customers worldwide. We are currently looking for an experienced, highly motivated Senior Engineering Manager to lead our ML Engineering team based in India. This is an established team with existing engineers — we expect the candidate to ramp up quickly on our ML infrastructure stack, build strong relationships with the team, and partner with both India-based teams and US-based teams to drive execution and grow the team further. This individual will join us on our journey to build and scale ML infrastructure that serves real-time predictions at low latency, automates model deployment and promotion, and provides the observability and reliability guarantees that production ML systems demand. Become part of a team that bridges the gap between ML research and production engineering — shipping systems that directly impact GoDaddy's core revenue. What you'll get to do... Lead a team o

End to end responsible for: • owner-side oversight of MEP execution outcomes by ensuring sequencing, interfaces and performance requirements are met through PMC supervision of GC. • review of critical method statements, ITPs, submittals and deviations for compliance and constructability. • commissioning and handover readiness for MEP systems, including documentation, training and defect closure. Source: Adani Group | Job ID: 57978

As a Colliery Engineer, the core objective is to oversee and manage various engineering aspects of coal mining operations, ensuring compliance with safety standards, regulatory requirements, and company policies. Key responsibilities include planning, installation, and maintenance of critical infrastructure such as electrical systems, pipelines, and machinery to facilitate safe and efficient mining activities. Additionally, the role involves coordinating monsoon arrangements, water management, and environmental initiatives, while also focusing on budgeting, compliance, and technological advancements to optimize operational efficiency and sustainability. Source: Adani Group | Job ID: 57885

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. About Okta & Our Culture At Okta, partners are central to our success. The Global Partner Program team equips partners with the operational foundation, resources, and clarity needed to build thriving, long-term Okta practices. Embedded in our Okta culture, we champion conscious leadership, high self-awareness, active empathy, and radical accountability. We focus on the whole human—fostering transparent relationships with our partners while enabling high-velocity growth. Role Overview We are seeking a Global Partner Sales Desk Specialist who brings an outward mindset and strong operational rigour to our partner-led deal flow. Reporting to the Manager of Global Partner Operations, you will be the connective tissue between external partners and internal stakeholders—leading Deal Registration qualification, streamlining quoter-to-order workflows, and driving data integrity across systems. The ideal candidate is a self-aware communicator who thrives in a dynamic environment, embraces continuous learning, and takes pride in elevating both partner and team performance. Location & Structure: Hybrid role with cross-regional timezone support (rotational shifts). Reports to: Manager, Global Partner Operations Key Responsibilities Empathy-Led Deal Registration Management: Review and validate Deal Registrations (DR) with speed and precision, ensuring program compliance while actively removing friction for partners. Serve as an approachable guide to troubles

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 We are looking for a Senior Release Engineer to help design, standardize, and operate reliable enterprise application delivery across the Enterprise Technology & AI team. This role will establish scalable CI/CD practices for business-critical platforms such as Salesforce, Zuora and other Business Systems while enabling engineering teams to ship changes safely, quickly, and with clear operational controls. The ideal candidate combines strong release engineering and automation skills with practical experience supporting enterprise SaaS applications. You will build and maintain GitLab CI/CD or comparable

About the Role: We are looking for an experienced Risk Management professional to lead and strengthen our Market Risk and Margin Trading Facility (MTF) risk functions. The role will be responsible for developing robust risk frameworks, monitoring trading and client exposures, ensuring regulatory compliance, and safeguarding the organization against market-related risks while enabling sustainable business growth. Key Responsibilities: Market Risk Management - - Develop, implement, and continuously enhance market risk management frameworks across Equity, Derivatives, and Margin Trading Funding (MTF) businesses. - Monitor and assess market risk exposures arising from cash equities, futures, options, and leveraged products. - Establish and review risk limits, exposure thresholds, concentration limits, and margin policies. - Track key risk indicators (KRIs) and ensure timely escalation of potential risk events. MTF & Exposure Risk Management: - Manage client-level and portfolio-level risks associated with Margin Trading Funding (MTF). - Define collateral eligibility, haircut frameworks, and funding exposure limits. - Monitor leveraged positions and ensure adequate margin coverage across client portfolios. - Evaluate concentration risks and implement preventive controls to minimize losses. Risk Analytics & Monitoring: - Conduct stress testing, scenario analysis, and sensitivity assessments under varying market conditions. - Develop risk models and analytical tools to evaluate portfolio resilience during periods of volatility. - Analyze trading patterns, market trends, and exposure data to identify emerging risks. - Drive automation and real-time risk monitoring capabilities across trading systems. Regulatory Compliance & Governance: - Ensure compliance with SEBI, NSE, BSE, Clearing Corporation, and other applicable regulatory requirements. - Oversee risk-related regulatory reporting, including exposure monitoring, margin compliance, and CTCL reporting. - Coordinate w

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

Location Details: Remote, 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 remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team... This role is for a Staff Technical Program Manager within GoDaddy’s engineering organization, focused on building scalable, fault-tolerant systems that power critical customer and platform experiences at massive scale. GoDaddy is empowering everyday entrepreneurs around the world by providing all of the help and tools to succeed online. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success! What you'll get to do... As a Staff Technical Program Manager, you will be at the forefront of our project management efforts. You will coordinate the seamless delivery of technical programs, ensuring our projects are successfully implemented and meet the highest standards. Your role is pivotal in driving our mission forward by: Leading and coordinating multiple workstreams across product engineering, legal, and enterprise customer commitments. Owning the program layer of cloud environment security efforts, including control rollout, remediation SLAs, and audit readiness. Building mechanisms for seamless execution such as product-style intake, prioritization frameworks, and launch readiness reviews. Partnering closely with product management, build, and engineering leadership to ensure successful project launches and smooth deprecation of prior tooling. Holding your own in architecture reviews, build docum