Ai Research Intern in India

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it. Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for a Principal AI Engineer, who craves variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. You Will: Own the target-state architecture for Smartsheet's AI platform, defining the standards that bind Data, Agents, Knowledge Graph, Context Graph into one coherent system. Set the architecture for the agent harness and sub-agent framework including orchestration, lifecycle, hand-off contracts, Evals (Offline and Online) and capability-tier classificati

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role The future of analytics isn't dashboards. It's intelligent systems that anticipate questions, surface insights, and help people make better decisions. We're looking for a Senior Analytics Engineer to help build that future at Pearl. In this role, you'll design and develop AI-powered analytics experiences that combine trusted enterprise data with modern AI capabilities, enabling business users to interact with data conversationally and uncover insights faster than ever before. You'll build production AI agents, create scalable semantic data models, develop intelligent analytics applications, and establish best practices for responsible AI across the Analytics organization. Working closely with Product, Engineering, and business leaders, you'll turn emerging AI technologies into real business capabilities that improve decision making across the company. This is an opportunity to help define how AI transforms analytics at Pearl while working on some of the most exciting technologies in data, LLMs, and agentic AI. What You’ll Do Build proactive analytics and AI solutions that surface actionable business insights, anticipate business needs, and enable smarter decision-making. Design and develop AI-powered analytics tools, including conversational interfaces that allow business users to query data using natural language. Build semantic data models and reusab

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure is moving from an application-centric world to a data-centric one — where AI depends on trusted, well-governed, and contextualized data across the business. As part of this shift, we're looking for a Staff Analyst, AI & Automation to lead the technical build of AI and applied ML capability inside the analytics function. This is an individual contributor role — you will not manage people. Your leverage comes from what you build and ship: AI agents, applied ML models, and automated analytics workflows that change how insight gets produced, working closely with cross-functional teams to bring these to life. AI is changing by the week, not by the year. We're not looking for someone who adopts AI once it's already mainstream — we want someone who is naturally ahead of the curve: scanning what's new, testing it quickly, and bringing it into the team before it's obvious to everyone else. This role has real freedom to experiment, rethink existing approaches, and change course as the field moves. WHAT YOU'LL DO Own the technical build of AI-powered analytics tools — including RAG pipelines, LLM-assisted querying, agent workflows, and applied ML models. Our current stack includes Glean, Gemini, Claude Code and Snowflake Cortex, and we expect that to change; we care more that you pick up new tools quickly than that you already know ours. Apply data science methods (forecasting, segmentation, anomaly detection, c

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pure Solutions team as a Senior MLOps Solutions Engineer to architect and build high-scale, enterprise-grade AI/ML solutions. You will be instrumental in integrating Pure Storage platforms with the evolving open-source MLOps ecosystem (Kubeflow, MLflow, Ray) to operationalize the complete machine learning lifecycle. This role requires a creative technologist with deep Python expertise to drive innovation and enable our customers and partners to achieve production AI success. WHAT YOU'LL DO Design and Automate MLOps Pipelines: Lead the development of end-to-end MLOps workflows using CI/CD tools (Git/Jenkins) and orchestration platforms (MLflow/Kubeflow), specifically integrating Pure Storage's FlashBlade, FlashArray, and Portworx as the high-performance data plane for data ingestion, training, and inference. Build High-Performance AI/ML Reference Architectures: Create validated, repeatable deployment models using Infrastructure as Code (e.g., Ansible, Terraform) for AI/ML environments spanning bare metal, virtual machines, and GPU-accelerated Kubernetes clusters, ensuring optimal performance for distributed training. Optimize and Operationalize GPU Inference: Architect and implement solutions for high-throughput, low-latency model serving, utilizing technologies like NVIDIA Triton Inference Server and advanced optimization techniques (quantization, model sharding like DeepSpeed/Megatron-LM, and dynamic bat

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As an Agent / AI Engineer , you will build the AI layer of the GCC Intelligence Platform—the conversational agent users interact with. You will own grounding, retrieval, persona routing, session state, and permission-aware querying so the agent stays accurate, secure, and tenant-safe. What You’ll Do LLM & Agent Integration Integrate LLM APIs (e.g., AzureOpenAIor equivalent) for conversational workflows. • Build a grounding layer that anchors responses to real platform data (not model guesses). • Maintain prompt templates across multiple personas and use-cases. Retrieval, Permissions & Security Boundaries Implement intent classification and persona routing to the right KPI views. • Build the API

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

Opportunity Overview: We are seeking a Senior Software Engineer - AI to join our Engineering team. In this role, you will build the intelligent agents and applications serving health insurance plans covering over 15 million people. You'll partner closely with product, data science, and clinical teams to build the foundation that transforms how clinical intelligence is delivered at scale. This is an opportunity to make a direct impact on healthcare outcomes while working with modern technologies in a fast-paced, collaborative environment. What you’ll do: Agent Development : Participate in the development, evaluation, and deployment of Cohere’s AI-powered agents and applications. Data & Retrieval Architecture : Design data and retrieval architectures that give AI agents the right context across diverse healthcare sources. Hands-On Engineering : Design, review, and own high-quality agentic code — leading releases, production deployments and on-call support. Cross-Functional Collaboration : Work closely with ML/DS teams, product teams, and architects to understand requirements and ensure systems meet business needs. Security & Compliance : Ensure all agentic components comply with healthcare security and privacy regulations (e.g., HIPAA) and adhere to industry best practices for security. Agile Development : Contribute to sprint planning, execution, and retrospectives, driving efficiency and velocity within the engineering team and collaborating closely with stakeholders to align with product goals and business priorities. ISMS roles and responsibilities: Good knowledge of Information practices. Assist the manager in all the information security activities implementation and maintenance process. Ensuring the team and imparted with Competence related to Information security Responsible for implementation of security policies and procedures and report any issues to the Information Security Manager. Required Qualifications: Must-haves Bachelor’s degree

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior AI Engineer, you'll join a 10-person team focused on data integrations (shippers and carriers moving in and out of the FourKites ecosystem) and our active AI agent workstreams — including a support automation agent handling 60-70% of customer tickets, a voice agent that calls carriers to gather and update information, and an end-to-end carrier onboarding agent (email + voice). You'll work on features end to end (~75-80% backend, ~20-25% frontend) using Python, Java/GoLang, agentic frameworks like LangGraph, React, Redis and PostgreSQL. You'll develop products that change the logistics landscape for some of the biggest corporations in the world, and work closely with our US team and customers to shape the future of the industry. What you’ll be doing: Design, build, and productionize AI agents/workflows (e.g., support automation, voice, and onboarding agents) using agentic frameworks such as LangGraph Develop, test, and maintain backend applications in Python and Java or GoLang Write clean, efficient, and well-documented code across the full SDLC — development, QA, and release Design and implement data models and database schemas Collaborate with the frontend team to integrate the backend with the user interface Perform code reviews and ensure code quality standards are met Troubleshoot and debug applications, including AI agent workflows in production Work with the DevOps team to deploy and manage applications in production (Kubernetes) Continuously learn and stay up to date with new technologies and industry trends, particularly in the AI/agentic space About the team: Our

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing. What you'll be doing: Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks. Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems. Collaborate with business and IT teams to translate business requirements into AI-driven solutions. Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation. Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization. Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support. What we need to see: Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field. 6+ years of software engineering experience with strong proficiency in Python and backend application development. Hands-on experience with Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development. Experience integrating enterprise applications and building scalable, production-ready software solutions. Strong analytical, problem-solving, communicatio

Fiduciary Trust International is a premier investment and wealth management firm with a commitment to growing and protecting wealth across generations. We offer a dynamic and collaborative approach to managing wealth for high-net-worth and ultra high-net-worth individuals and families, family offices, endowments, foundations, and institutions. Our investment managers, tax and estate planning professionals work together to develop holistic strategies to optimize clients’ portfolios while mitigating the impact of taxes on their wealth. As a fiduciary, the guidance we provide is in the best interests of our clients, without conflict or competing benefits. We offer boutique customization and deep expertise in specialized investment, tax and planning strategies alongside sophisticated technology and custody platforms. Fiduciary Trust International is owned by Franklin Templeton, a dynamic firm that spans asset management, wealth management, and fintech, giving us many ways to help investors make progress toward their goals. With clients in over 150 countries and offices on six continents, you’ll get exposed to different cultures, people, and business development happening around the world. About the Department: Our AI Engineering team develops and scales production-ready Generative AI and Agentic AI solutions that help solve complex business challenges and accelerate innovation across the organization. The team brings together AI engineers, architects, and business stakeholders who work collaboratively to design, build, and deploy secure, enterprise-grade solutions on Microsoft Azure. Joining this team offers opportunities to work with emerging technologies, influence AI standards and best practices, and contribute to high-impact initiatives in a collaborative and growth-oriented environment. How Y

We're Hiring Senior AI Engineer (Generative AI Azure) Remote Immediate Joiners Preferred Salary: Up to 12 LPA We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions on Microsoft Azure. The ideal candidate will have strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Azure AI Services, and modern AI engineering practices. Technical Summary • AI & LLMs: Azure OpenAI, GPT-4.x, OpenAI, Prompt Engineering, Prompt Chaining, Function Calling, Structured Outputs, Tool Calling, JSON Schema, Model Evaluation, Guardrails, Fine-tuning Concepts • Agentic AI: Multi-step Reasoning, Planning, Memory Management, Tool Orchestration, Multi-Agent Systems, Human-in-the-Loop Workflows, Reflection, Context Management, AI Observability • Frameworks: Semantic Kernel, LangChain, LangGraph, AutoGen, Azure AI Agent Service • RAG & MCP: Retrieval-Augmented Generation, Vector Search, Semantic Search, Hybrid Search, Embeddings, Knowledge Grounding, Citation Generation, Document Ingestion, Chunking, MCP Architecture, MCP Servers & Clients • Azure Technologies: Azure AI Foundry, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning, Azure Functions, API Management, Logic Apps, App Service, Container Apps, AKS, Azure Storage, Data Lake Gen2, Azure Key Vault, Azure Entra ID, Azure Monitor, Application Insights, Event Grid, Service Bus • Programming & DevOps: Python, C#, REST APIs, FastAPI, ASP.NET Core, JSON, YAML, Git, Azure DevOps, Docker, Kubernetes • Data Platforms: SQL Server, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, Microsoft Fabric, Azure Databricks, Delta Lake, Vector Databases (Azure AI Search, Pinecone, Weaviate, Milvus, Qdrant) • Security & Governance: Responsible AI, Prompt Injection Prevention, RBAC, Content Filtering, Data Privacy, GDPR, ISO 27001, Azure Key Vault, Audit Logging & Monitoring • Nice to Have: Microsoft Copilo

Generative AI Architect Strong expertise in GenAI frameworks (OpenAI, Azure OpenAI, LangChain, LangGraph, Copilot Studio) and AI platforms. Key Responsibilities Design and deliver end-to-end Generative AI and Agentic AI architectures for enterprise clients. Lead technical implementation using Azure OpenAI, LangGraph, or Copilot Studio. Build reusable frameworks, prompt orchestration patterns, and RAG pipelines. Ensure compliance with security, privacy, and Responsible AI standards. Drive AI observability, cost optimization, and performance tuning. Collaborate with data, cloud, and business teams to identify AI use cases. Mentor engineers and contribute to practice accelerators and reference solutions. Support presales, client demos, and proposal development with architecture inputs.

- Proven experience deploying and managing Kubernetes clusters for AI/ML workloads. Experience of at scale deployments with Azure Kubernetes. Experience level - 5 Years or more Positions - 2 Proven experience deploying and managing Kubernetes clusters for AI/ML workloads. - Experience of at scale deployments with Azure Kubernetes Service, RedHat OpenShift, Microk8s and Helm Charts. - Expertise with infrastructure and resource management and virtualization tools such as VMWare/EXSi, KVM, Ansible, Redfish. - Strong understanding of Run:AI platform, including job scheduling, quota management, and GPU virtualization. - Knowledge of NVIDIA AI Enterprise components including, NIM, NeMO, TAO, Triton and Nucleus Servers - Familiarity with DGX systems, Jetson, and NVIDIA’s AI Factory components. - Proficiency in Python, C++, and optionally .NET/C# for enterprise integration.

Location Details: India, Remote At GoDaddy, the future of work varies by team. Some teams are fully office-based. Others split their time between remote work and the office. Some teams work completely from home. 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... At GoDaddy, we are seeking a Senior Analyst to join our Assurance, Risk and Compliance (ARC) Enablement team. This role will help transform how our team and business improve processes, use technology, and empower people to manage risk and build the future compliance program. Reporting directly to the Director of ARC, you will drive meaningful improvements in people, processes, and technology. You will redesign workflows that cause unnecessary manual effort. You will develop automation and analytics that make compliance ongoing instead of occasional. You will ensure the team and collaborators are prepared to maintain and expand what is developed. You will work with SOX, Internal Audit (IA), and Enterprise Risk Management (ERM) to deliver scalable, auditable, and AI-forward solutions. If improving how compliance functions motivates you, this is your role! What you'll get to do... Find the friction and fix it. Map current-state workflows across ARC's SOX, IA, and ERM functions. Identify where manual effort and inefficiency exist. Lead process improvements that remove them for good. Build automation that actually sticks — develop pipelines, CI/CD-enabled code repositories, and repeatable testing frameworks that turn periodic compliance efforts into continuous, always-on operations. Make compliance visible in real time — build Power BI dashboards and analytics pipelines (Python, SQL) that give leadership and control owners a live view of risk posture. Put Jira to work for compliance — configure workflows, automation rules, and intake forms that embed traceability and standardization di