Engineering Excellence Engineer 2 in India

JOB TITLE Cloud Engineer A Career with point72’s technology team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What You'll Do Design, implement, and maintain scalable cloud infrastructure using Infrastructure as Code (IaC) with Terraform. Manage and optimize foundational platform for AWS/GCP/Azure services including IAM, Virtual Private Cloud networking, Cloud Security controls and policies, Cloud platform tools and automation to ensure scale, performance and security. Collaborate with development and operations teams to automate deployment and operational processes. Monitor cloud environments to maintain high availability and security standards. Participate in architectural discussions and contribute to the technical roadmap for cloud solutions. Implement best practices for cloud resource optimization and cost management. What's Required Bachelor’s degree in Computer Science, Engineering, or a related field. 5 to 10 years of experience in cloud infrastructure design and automation with optional experience in cloud networking. Proficiency in Infrastructur

A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. WHAT YOU’LL DO • Create and execute automated and manual test cases to ensure optimal system performance according to specifications. • Work closely with software development and support teams to deliver high-quality applications in a timely manner. • Develop and maintain comprehensive test plans, including manual and automated tests for functional, regression, and integration testing. • Build consensus between stakeholders and developers to define clear and testable acceptance criteria. • Document quality assurance and process flows, both existing and proposed. • Advocate for best quality assurance practices and testing techniques. • Ensure any new software changes meet business, legal, compliance, and technical requirements. • Develop and maintain test automation frameworks for various applications in trading domains. • Maintain and track quality assurance capacity, velocity, statuses, and deliverables with the team lead. WHAT’S REQUIRED • 5+ years of experience in quality assurance with test automation, software engineering, or business analysis roles. • Comprehensive expertise in processing trades, managing trading and lifecycle events, handling corporate actions, and managing cash flows. • Experience supporting fixed income products, Equities and Treasuries. • Solid understanding of position management for listed and OTC products. • Understanding of SDLC, Test lifecycle, and testing methodologies. • Experience creating and writing SQL que

You’ll shape the future of a business‑critical platform as the technical lead across both product engineering and cloud infrastructure. You’ll modernize a mature .NET application running on AWS today, while steering its evolution toward a cloud‑native, React/Node.js, AI‑enabled architecture. If you enjoy owning architecture end‑to‑end, from backend and frontend through CI/CD, DevOps, and AWS infrastructure, this role gives you real influence at Staff Engineer level and the opportunity to set engineering standards that others follow. You’ll spend your time leading complex .NET and React features, designing scalable AWS infrastructure with Infrastructure as Code, and building automation that makes releases fast, safe, and repeatable. You’ll work on performance, reliability, and modernization in equal measure—fixing what’s slowing the platform down today and designing what it will look like in the next generation. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and development of enterprise .NET services and APIs that power a business‑critical platform. Design and operate AWS infrastructure (using AWS CDK in TypeScript) to support secure, scalable, multi‑environment deployments. Build and optimize CI/CD pipelines (AWS CodePipeline, CodeBuild, Windows build agents) to make shipping .NET and React changes fast and reliable. Drive modernization initiatives across the stack, including clean architecture, refactoring legacy components, and reducing technical debt. Design and tune PostgreSQL and MSSQL database solutions for performance, scalability, and reliability. Mentor engineers and influence engineering practices across teams, raising the bar on cloud, DevOps, and software design. These are the essentials you’ll need to get an interview Significant experience (typically 8+ years) delivering and operating scalable enterprise software, owning both application code and cloud infrastructure. Deep hands‑on expertise with C

About Us: Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at saucelabs.com . The Role: We are seeking an innovative and experienced AI Architect to join our engineering leadership team. This is a strategic role that will be instrumental in designing and building the next generation of AI-powered features for our continuous testing platform. You will be responsible for architecting scalable and robust AI solutions that transform how our customers gain insights from their test data and production environments, and how they create tests. Responsibilities: Define AI Architecture: Lead the design and architecture of cutting-edge AI/ML solutions for new product offerings, ensuring scalability, performance, quality and reliability within a cloud-native environment. AI-Powered Insights (Test & Production): Architect AI systems to derive actionable insights from vast quantities of test run logs and analytics data. This includes identifying patterns, anomalies, and performance trends. Production Error Reporting Integration: Design AI solutions that integrate with our existing error reporting product to analyze production issues for mobile and web applications, providing deeper understanding and predictive capabilities. Unified Data Intelligence: Develop architectures for combining insights from both test runs and production data, creating a holistic view of application quality and user experience. Automated Failure Analysis & Remediation: Architect AI models and systems t

Opportunity Overview: We are seeking a Sr Business Intelligence Engineer to join our Intelligence team. In this role, you will drive the development and optimization of our analytical infrastructure, enabling efficient, scalable, and consistent reporting and analytics across the organization. You will play a critical role in shaping the foundation of our BI ecosystem—working at the intersection of engineering, data modeling, and stakeholder enablement. This is an ideal opportunity for an experienced BI engineer who can execute cross-functional projects, design performant data models, and contribute to the execution of a unified data strategy across platforms. You will also provide guidance and mentorship to junior team members and contribute to the evolution of Cohere’s modern data stack and governance practices. What you’ll do: Lead the execution and refinement of our business intelligence and analytics architecture, ensuring consistency, performance, and scalability across dashboards and self-service tools. Design and implement robust semantic and dimensional data models supporting operational, clinical, and strategic analytics use cases. Collaborate closely with data platform, analytics, and product teams to define shared data definitions, build source-of-truth datasets, and align transformations with stakeholder needs. Improve data pipeline efficiency and maintainability by establishing and enforcing best practices in dbt modeling, testing, and documentation. Support release management, quality testing, version control, and promotion of analytics assets across environments. Enable data providers and analysts to deliver high-impact dashboards and KPI frameworks using Tableau, with an emphasis on performance, usability, and governance. Serve as the primary Tableau Cloud SME for the organization, including user management, security, performance tuning, and environment configuration. Lead integration of Tableau dashboards into front-end web applications using the Ta

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

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c

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

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

We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineerin

Perforce is a community of collaborative experts, problem solvers, and possibility seekers who believe work should be both challenging and fun. We are proud to inspire creativity, foster belonging, support collaboration, and encourage wellness. At Perforce, you’ll work with and learn from some of the best and brightest in business. Before you know it, you’ll be in the middle of a rewarding career at a company headed in one direction: upward. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce Software, Inc. is trusted by the world’s leading brands to deliver solutions for the toughest challenges. The best run DevOps teams in the world choose Perforce. Responsibilities Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 6+ years of hands-on software development experience. Strong foundation in Java and API technologies. Genuine interest in specializing in mainframe/legacy systems technology as a long-term career direction. Core Technical Skills – Java, APIs & Modern Stack Working knowledge of Java, used for the Sola IDE and one of the Sola runtime implementations. Experience with RESTful and SOAP web services, including how they're designed, secured, and exposed from backend systems. Familiarity or hands-on experience with API management gateways (e.g., Akana, Apigee, MuleSoft, Kong, or similar) — Sola's core purpose is exposing mainframe assets as governed, gateway-managed APIs. Working knowledge of JavaScript, used extensively within the Sola IDE. Experience with SQL/NoSQL databases, including DB2, Oracle, MS SQL, and/or MySQL. Working knowledge of CI/CD tools and pipelines. Requirement Mainframe & Legacy Systems – Growth Track (Mentorship & Training Provided) These skills will be

NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Senior Solution Architect with full-stack software engineering experience to join our team and play an important role in developing Sales AI applications. This position offers the opportunity to design, build, and evolve solutions that bring generative AI and intelligent workflows into everyday sales experiences. You will work across the application stack and collaborate with Product, AI and machine learning, Data, Security, Solution Architecture, and Engineering teams to deliver secure, reliable, and scalable solutions used globally. What you’ll be doing: Collaborate with application teams to design, develop, and maintain scalable full-stack solutions for enterprise sales workflows. Guide technical solutions across front-end, back-end, APIs, data services, integrations, and cloud infrastructure. Translate product requirements and business needs into secure, maintainable solutions and intuitive user experiences. Integrate generative AI models, AI services, APIs, retrieval systems, and agentic workflows into production applications. Design application architectures that support performance, availability, observability, security, scalability, and long-term maintainability. Lead technical design discussions, compare implementation approaches, make informed architecture decisions, and evaluate emerging technologies. Improve engineering practices for testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Investigate complex issues and develop solutions that improve reliability and user experience. Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices. What we need to see: <

Job Details: Job Description: In this role, you'll build software capabilities to automate the build, test, and deployment of Intel's Process Design Kit (PDK). A PDK is a collection of artifacts representing Intel's semiconductor process, used by product designers to model, implement, and verify Intel's mobile, desktop, and server products before manufacturing. You'll be a member of the Design Technology Platform organization, working closely with teams in the United States, Bangalore, and Penang to build world-class DevOps infrastructure that shapes the future of deploying PDKs to silicon product development teams at Intel. Qualifications: Bachelor's or Master's degree in Computer Science, Computer Engineering, or another closely related field. 7-12 years of experience with a Bachelor's degree or Master's degree in software development and engineering. Excellent Python programming skills. Expert-level knowledge of pytest concepts. Expert-level experience with GitHub-based Jenkins CI/CD deployment, enablement, and debugging. Proven knowledge of Agile software engineering practices, IT environments, and DevOps principles and processes. Excellent debugging and problem-solving skills. Excellent written and verbal communication skills; ability to present complex issues with clarity to drive decisions. Must have hands-on experience with AI tools and demonstrated experience building AI agents/tools. Exposure to VLSI PDK domain is preferred. Strong team player with proven ability to collaborate effectively across cross-functional and geographically distributed teams. Job Type: Experienced Hire Shift: Shift 1