Top Artificial Intelligence Jobs in Delhi

Build and ship Kotlin-based native Android features for a finance super app: implement insurance, payments and financial flows, integrate backend APIs, improve performance and reliability, collaborate with product/design, and apply on-device ML where helpful.

Build end-to-end customer-facing and internal features across frontend and backend for a finance super app. Develop web flows, APIs, admin tools, dashboards and operational systems. Integrate third-party APIs, handle data flows, improve production reliability and post-launch features using analytics and feedback. Collaborate with product, design, mobile and operations teams and support production issues.

Lead product direction for major finance super-app areas in India, define roadmaps and success metrics, guide PMs and cross-functional squads, translate regulatory and operational constraints into product decisions, drive launch quality and continuous improvement across payments, savings, investing, insurance and travel.

Own product areas across BJAK's finance super app (insurance, payments, savings, investing, travel). Define problems, scope, metrics, roadmaps and launch plans. Collaborate with engineering, design, data, operations, compliance and business teams. Simplify complex financial products, use data and feedback to iterate, monitor performance, and balance speed, UX, business impact and compliance.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.

The Senior AI Engineer will lead the design and development of AI systems, mentor engineers, and drive innovation in AI technologies for gaming applications.

The AI Engineer will develop and deploy advanced AI solutions focusing on generative capabilities, build context-aware AI agents, collaborate on data management, optimize AI model performance, and stay updated with AI advancements.

Lead enterprise AI strategy, design scalable AI solutions (LLMs, agentic AI, federated learning), evaluate emerging technologies, establish AI governance/Responsible AI, drive XAI adoption, collaborate with stakeholders, and implement advanced generative and orchestration solutions.

Design, build, and operationalize AI-enabled data pipelines and production-grade AI applications using Python and Snowflake. Prepare and transform large datasets, develop features and embeddings, support deployment and monitoring of ML/LLM models, optimize Snowflake for AI workloads, and collaborate with data science and engineering teams to deliver scalable APIs and RAG-enabled data workflows.

As an AI Data Expert, you will evaluate AI-generated outputs, provide culturally relevant feedback, ensure content accuracy, and participate in quality assurance. This role requires strong analytical skills and attention to detail.

The AI Data Expert position involves evaluating AI outputs, generating content, and providing annotations to enhance AI training, all while considering cultural context. This role requires detail-oriented analysis, native language fluency, and strong English command.

As an AI Data Expert, you'll evaluate AI-generated outputs, review text, analyze multimedia, and provide structured feedback based on cultural standards.

The role involves evaluating AI outputs, generating content, providing annotations, and ensuring quality through cultural and contextual awareness.

The role involves reviewing AI outputs, generating content, ensuring cultural accuracy, and providing structured feedback to improve AI models.

Review and evaluate AI-generated outputs, provide annotations, and contribute cultural insights to improve AI training. Requires detail-oriented judgment and strong language skills.

Design, build, and scale AI capabilities and services for a multi-tenant SaaS platform. Implement LLM/RAG solutions, deploy models, integrate data pipelines and datastores, ensure reliability, mentor engineers, and collaborate across teams to deliver production-grade, cloud-native AI systems.

Remote 14-day pilot requiring native/expert Indian English speakers to use a qualifying Google Pixel device as their primary phone, interact naturally with notification-generating apps, complete ~10–15 minutes of daily notification-sorting tasks and short feedback forms via Upwork, and report issues. Participants must own the device, have reliable internet, and be international freelancers (not U.S. residents).

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

The AI Architect will design, implement, and oversee large-scale AI systems, ensuring they align with business goals and ethical standards. Responsibilities include architectural design, integration of AI models, and collaboration with data engineering. Requires over 10 years of experience in AI/ML implementations for large enterprises.

Lead a team for developing LLM and multimodal AI systems for healthcare. Ensure clinical safety, regulatory compliance, and effective deployment in telemedicine.

Gather and analyze stakeholder requirements and translate them into ServiceNow AI solutions (Virtual Agent, Predictive Intelligence, Now Assist). Collaborate with technical teams to implement AI-driven automation and agentic solutions, optimize workflows, monitor system performance, train users, and drive adoption while ensuring clear communication between business and technical stakeholders.

Lead development of GenAI and LLM-powered applications using Python, LangChain/LangGraph and FastAPI. Design scalable cloud-ready microservices, integrate LLMs (AWS Bedrock/OpenAI), implement prompt engineering, and build interactive frontends with Angular/JavaScript. Ensure AWS-based deployment and database integration (SQL/NoSQL).

Lead end-to-end product design for web and AI-driven experiences, create high-fidelity UI and prototypes in Figma, collaborate with frontend engineers (React + Tailwind CSS), evolve the design system, conduct user testing, and integrate AI-driven interactions while working remotely with cross-functional teams.

Lead architecture, design, and governance for enterprise-scale AI solutions on the ServiceNow platform, implementing Now Assist, Virtual Agent, Agentic AI, predictive and task intelligence, integrations, and AI governance frameworks.

Design and lead enterprise-grade AI and Gen-AI integrations using the MCP (Model-Context-Prompt) framework. Architect LLM integrations, define prompt engineering and context strategies, evaluate models, design scalable secure solutions, oversee deployment/monitoring/optimization, mentor development teams, translate business needs into technical designs, and provide night-shift production support.