Engineering Architect in India

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

URGENT HIRING Interior & Civil Site Supervisor Kolkata Recruitment Partner: IDEAL CAREER ZONE A reputed company is looking for an experienced Interior & Civil Site Supervisor to manage interior fit-out and civil construction projects. Location: Kolkata Position: Interior & Civil Site Supervisor Qualification: Diploma / B.E. / B.Tech in Civil Engineering or related field Experience: Minimum 5 Years Salary: As Per Industry Standard Job Responsibilities Supervise day-to-day interior fit-out and civil site activities Ensure execution as per approved drawings, quality standards, and project timelines Coordinate with architects, engineers, contractors, and vendors Monitor manpower, materials, and site progress for timely project completion Conduct quality inspections, verify measurements, and ensure safety compliance Resolve site issues and maintain smooth project execution Preferred Candidate Candidates with experience in both Interior Fit-out and Civil Construction will be given preference. Required Skills Strong leadership, communication, coordination, and problem-solving skills Ability to handle multiple site activities efficiently Interested candidates can send their updated CV to IDEAL CAREER ZONE or visit our office for registration and interview assistance. HR Contact: 9231799122 // 9331205133 // 8777211016 Call Timing: 10:00 AM 8:00 PM Visit Timing: 12:00 PM 7:00 PM (Monday to Saturday) #Hiring #SiteSupervisor #InteriorJobs #CivilEngineer #ConstructionJobs #CivilJobs #InteriorFitOut #EngineeringJobs #KolkataJobs #ImmediateHiring #CareerOpportunity #IdealCareerZone

AI/ML Dev - Chatbots • 8+ years of experience in Data/AI Projects • Understanding of end-to-end architecture for Generative AI solutions aligned with business goals. • Experience in Azure OpenAI integration (GPT models, embeddings) with prompt engineering and model tuning. • Programming experience in Python for AI project is a must • Designs scalable RAG systems using Azure AI Search, vector databases, and secure data pipelines. • Knowledge of MLOps and CI/CD workflows using Azure DevOps and automated testing frameworks. • Establishes Python coding standards, reviews code, and mentors development teams. • Knowledge of deployment and governance of AI applications across Azure infrastructure. • Work with cross function teams (IT/ Non IT) to help the development teams build the solutions faster and more efficiently.

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. Workforce Identity Cloud Okta Workforce Identity Cloud (WIC) provides easy, secure access for your workforce so you can focus on other strategic priorities, such as reducing costs and doing more for your customers. If you like to be challenged and have a passion for solving large-scale automation, global traffic routing, and resilient cloud infrastructure problems, we would love to hear from you. The ideal candidate is someone who exemplifies the ethics of, “If you have to do something more than once, automate it” and who can rapidly self-educate on new network topologies, multi-cloud ecosystems, and agentic engineering models. Position Overview: The Staff Software Engineer - Infrastructure will play a foundational role in architecting, evolving, and securing Okta's global core network fabric and multi-cloud platform layers. This position focuses on building highly resilient, edge management in AWS and GCP cloud, executing enterprise-wide cloud migrations (AWS to GCP), enforcing absolute Zero-Trust primitives (mTLS / TLS 1.3), and integrating cutting-edge AI automation layers (Agentic SRE) into our day-to-day operations. As a Staff Engineer on this team, you will act as a key technical anchor in India, working closely with global counterparts to maintain Okta's high-availability SLAs while protecting the platform against active global DDoS attacks. Key Responsibilities: Global Ingress & Routerless Evolution (CFSaaS): Design and engineer Next-Gen traffic

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Designs and delivers scalable software solutions, applying strong engineering practices and technical judgment. Plans and executes defined projects with minimal guidance while collaborating across functions. This section contains a list of 5 to 8 primary responsibilities of this role that account for 5% or more of the work. The incumbent will perform other duties assigned. Plan and deliver defined software projects, including schedules, dependencies, and coordination with development and support teams. Design, architect, develop, test, and maintain scalable .NET applications, APIs, and microservices. Deve

Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

University Recruiter About Graviton : Graviton Research Capital is a global quantitative trading and investment firm driven by technology, mathematics and rigorous problem-solving. We bring together exceptional talent across quantitative research, software engineering and technology to solve some of the most challenging problems in the industry. Our university talent ecosystem is one of the most important engines for building Graviton's future — and one of the most operationally demanding to run well. The Role : We are looking for a campus talent professional who can both think in systems and execute in detail — someone who can shape how Graviton identifies, engages, assesses and converts exceptional early-career talent, and who is equally comfortable owning the on-the-ground execution that makes a hiring cycle run without friction. Depending on experience, this role can be scoped as a hands-on execution owner running the campus hiring engine end-to-end, or as a strategic owner architecting the assessment frameworks, university strategy and program design that the engine runs on — in both cases, you will partner closely with Quant and Tech leaders and be accountable for the full lifecycle: university outreach, assessments, internships, PPO conversion and onboarding. What You Will Own Campus Talent Strategy & Ecosystem Building Build and maintain relationships with priority institutions (IITs, IIITs, BITS and relevant global universities), placement offices, faculty and student communities. Drive year-round engagement - events, technical talks and competitions — to strengthen Graviton's employer brand outside peak hiring windows. Assessment & Selection Coordinate (or design and standardize, at senior levels) rigorous selection frameworks in partnership with Tech and Quant teams — scheduling assessments, allocating panels, driving timely feedback, and building interviewer calibration mechanisms to keep evaluation objective and consistent. Internships & PPO

JOB TITLE Cloud Compute 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, build, and operate Kubernetes clusters on Amazon EKS, including cluster lifecycle management, networking, autoscaling, and workload scheduling. Manage and optimize EC2-based compute infrastructure, including instance selection, placement strategies, capacity planning, and utilization analysis. Operate and improve ECS-based services where applicable, ensuring consistency across our container runtime environments. Develop and maintain Infrastructure as Code (IaC) using Terraform to provision and manage compute resources at scale. Collaborate with development and platform teams to define compute patterns, containerization standards, and deployment best practices. Monitor compute environments for availability, performance, and cost, driving continuous optimization across the fleet. Contribute to architectural decisions around workload placement, multi-tenancy, OS image and container li

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

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

Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec

We are looking for a Full Stack Developer to join our growing engineering team. In this role, you will design, build, and operate scalable software platforms that support analytics and AI solutions — owning the full journey from intuitive user interfaces to robust cloud-native backends. What This Involves: Front-End Development Develop and maintain user interfaces for web applications using React and Next.js. Translate wireframes and design mockups into functional, accessible UI components. Identify and resolve front-end performance bottlenecks to ensure smooth user experiences. Write and maintain unit and integration tests for front-end components (e.g. Jest, React Testing Library). Back-End Development Develop and maintain high-quality back-end services and APIs using Python. Deploy, operate, and monitor applications in cloud environments (AWS, Azure, or GCP). Manage containerized applications using Docker and Kubernetes. Contribute to the design and evolution of scalable, cloud-native software architectures. Contribute to and maintain CI/CD pipelines for web and back-end applications. Collaboration and Quality Work closely with data scientists, engineers and project managers to deliver integrated end-to-end solutions. Support the development and deployment of AI and analytics solutions. Write clean, well-documented, and maintainable code across the full stack. Participate in technical discussions, code reviews, and continuous improvement initiatives. Adhere to internal and client-mandated data protection and compliance policies, ensuring all handling, storage, and sharing of data meets required security and privacy standards. Requirements: Bachelor’s degree in Computer Science or related fields. 5+ years of software development experience, with meaningful time on both front-end and back-end systems. Experience designing systems in cloud-native or distributed environments is a plus. Excellent communication and collaboration skills — comfortable working acros

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