Top Artificial Intelligence Jobs in Delhi

Join Welo Data’s remote Afrikaans contributor network to support AI training projects through text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with compensation and timelines provided before each assignment. This is a talent-community application rather than an active job opening.

Join Welo Data’s Croatian talent network for potential remote AI projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy reviews. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent community registration rather than an active job opening.

Join Welo Data’s remote Hausa AI contributor network for future projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural accuracy review. This is not an active opening; selected contributors will receive project details, timelines, and compensation when suitable work becomes available.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Develop and deploy generative AI, LLM, conversational AI, and autonomous agent applications. Build scalable AI pipelines, fine-tune foundation and deep learning models, integrate agentic workflows, and optimize model performance for production. Collaborate with data engineers on datasets and stay current with advances in GenAI, LLMs, RAG, multimodal learning, and MLOps.

Build and improve scalable business operating systems across recruitment, HR, retail training, ecommerce, marketing, product, and reporting. The role converts founder-led knowledge and manual workflows into trackers, dashboards, SOPs, forms, source-of-truth documents, and AI-assisted processes. Responsibilities include process mapping, workflow testing, document control, access management, issue tracking, meeting-to-action systems, reporting, and user adoption. The role supports business owners but does not make final hiring, legal, strategic, or purchasing decisions.

Develop scalable full-stack web applications and AI-powered solutions using ReactJS, Python, FastAPI, PostgreSQL, APIs, cloud platforms, LLMs, RAG pipelines, and AI agents. Responsibilities include designing frontend and backend systems, optimizing databases, integrating internal and third-party APIs, deploying secure cloud applications, and following testing, code quality, security, and CI/CD best practices.

Develop and maintain Python applications, APIs, workers, integrations, and AWS Lambda functions. Manage AWS and Linux environments, infrastructure automation, deployments, CI/CD pipelines, and production support. Improve reliability through monitoring, canary releases, rollback, and recovery practices. Maintain databases, messaging, authentication, security, dependencies, and external integrations. Apply AI-assisted development tools with human review and security validation. The role requires ownership of software delivery from application code through production.

Transcribe unscripted Odia conversational audio verbatim in Odia script for AI speech model training. Responsibilities include preserving fillers and speech patterns, handling Odia-English/Hindi code-switching, tagging audio issues, following formatting guidelines, maintaining 97%+ accuracy, meeting turnaround times, and revising work based on QA feedback.

Build AI-powered products and backend services using Python and FastAPI. Develop RAG applications, integrate major LLM platforms, use vector databases and AI development tools, and create REST APIs. Collaborate with product and engineering teams to deliver features, while contributing to testing, debugging, deployment, and continuous improvement. The role may also involve AI agents, tool calling, MCP, cloud deployment, and Oracle Fusion integrations.

The ServiceNow Solution Architect - AI role involves leading and mentoring a team, designing and deploying AI-driven applications, managing application development, and integrating solutions into ServiceNow modules. Responsibilities include coordinating with stakeholders, troubleshooting, and ensuring adherence to technical standards.

Develop, train, deploy, and maintain machine learning and generative AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Design scalable ETL pipelines, optimize databases, process large datasets with Spark and Snowflake, and create business visualizations. The role requires expertise across Python, SQL, cloud AI platforms, machine learning frameworks, databases, and data engineering.

Develop, fine-tune, deploy, and optimize AI/ML models and LLM-based RAG solutions using Python and AWS Bedrock. Build REST APIs and microservices with FastAPI or Flask, deploy scalable cloud infrastructure, manage containerized workloads, and develop data pipelines and ETL processes. Work with relational and NoSQL databases, CI/CD, and AWS services while collaborating with technical and product teams and documenting AI workflows.

Design, develop, and deploy production-grade generative AI and agentic systems, including RAG pipelines, autonomous agents, prompt architectures, and enterprise integrations. Build solutions using LangChain, LangGraph, vector databases, cloud services, APIs, and DevOps tooling. Advise stakeholders, document and monitor AI applications, mitigate technical and security risks, modernize RPA assets, and mentor junior developers.

Designs and leads enterprise AI Factory and GPU infrastructure architectures spanning compute, networking, storage, Kubernetes, cloud, security, observability, and AI/ML platforms. Assesses workloads, develops reference architectures and detailed designs, performs capacity planning and technology evaluations, leads proof-of-concepts, and supports deployment, migration, troubleshooting, and production transition. Collaborates across infrastructure, security, cloud, data, application, and operations teams to ensure scalable, secure, reliable, and cost-effective AI platforms.

Design and build scalable data and AI infrastructure for production LLM applications. Responsibilities include developing RAG systems, embedding and vector retrieval pipelines, AI agents, LLM evaluation and observability frameworks, and batch or streaming data platforms using Databricks, Spark, Snowflake, Delta Lake, and Airflow. The role also involves optimizing distributed workloads, establishing data governance and quality practices, and partnering with engineering and product teams to productionize AI capabilities.

Leads the organization’s data science and AI roadmap, managing a hands-on team that develops statistical models, experiments, forecasting, segmentation, production AI solutions, and agentic workflows. Drives GCP-based model deployment, MLOps/LLMOps, governance, observability, ethical AI, and adoption of AI tools. Partners with business, engineering, product, BI, and analytics teams to deliver practical data products, define success metrics, and communicate technical insights to executives.

Own the Workato environment, configure enterprise integrations, and build AI-native packages using Workato AI Genie. Design and deploy agent-ready workflows and AI-powered workflow automation solutions, while managing RBAC, auditing, and multi-workspace environments. Integrate Workato with enterprise applications and support scalable workflow implementations.

Creates technical documentation, implementation guides, whitepapers, product content, landing pages, and blog posts focused on AI infrastructure and enterprise technology. Researches complex technologies, translates specifications and architectures into clear content, collaborates with technical experts, validates accuracy, and maintains consistent documentation standards for IT professionals, engineers, architects, and technology decision-makers.

Own the CRM Opportunities backend end to end, designing scalable data models, APIs, distributed workflows, event-driven services, and background jobs. Improve performance and reliability across large multi-tenant pipelines while handling consistency, caching, sharding, observability, and incident response. Build AI-assisted CRM features using existing LLM APIs, including context assembly, response handling, cost and latency controls, and graceful degradation. Occasionally ship Vue.js UI changes and operate services through deployment and on-call.

Lead ServiceNow AI/ML development, mentor engineers, and architect Agentic AI solutions. Build, train, and deploy machine learning models, NLP and LLM applications, chatbots, autonomous agents, ETL pipelines, and large-scale analytics across AWS, Azure, and Google Cloud. Work with Spark, Snowflake, databases, visualization platforms, and ServiceNow to deliver intelligent workflow automation for global enterprises.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.