Top Artificial Intelligence Jobs in Delhi

Customer-facing AI Engineer who designs, builds, and deploys production-grade LLM and agent-based solutions. Responsibilities include architecting agent systems, implementing RAG pipelines, integrating with platform signals and vector DBs, overseeing end-to-end ML lifecycle, writing clean Python code, and collaborating with customers and internal teams to ensure scalable, monitored deployments.

Lead architecture and solutioning for enterprise-grade, AI-enabled, cloud-native applications. Collaborate with clients, create feasibility assessments and POCs, ensure scalable, secure platforms, and mentor delivery teams while representing the company in client meetings.

Lead development of agentic workflows and LLM systems, build LLM evaluation/tracing and prompt operations pipelines, integrate MCP-based systems, deploy and scale enterprise-grade AI/ML solutions, and collaborate with product and engineering teams.

Architect, build, and operate end-to-end AI automation systems: CLI frameworks, MCP servers, agent tooling, production pipelines, evaluation and monitoring. Own prompt and context engineering, multi-agent orchestration, integration with external tools, governance, and metrics to measure automation and business impact.

The Content Writer/Ai Editor will create high-quality content while leveraging AI tools for optimization, managing multiple projects, and adhering to brand guidelines.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

Design and build production LLM-based agent systems, governance knowledge pipelines, hybrid retrieval and evaluation frameworks, and platform infrastructure. Implement behavioral shaping, observability, and constraints to ensure agents align with governance and compliance requirements, collaborating with product and data teams.

Design, build, and deploy end-to-end AI solutions—including predictive models, GenAI/LLM and agentic systems—integrating data preparation, feature engineering, model training, deployment, APIs, and monitoring for enterprise customers. Support implementation, demos, and cross-functional collaboration to deliver production-ready AI on the H2O.ai platform.

Design, build, and deploy end-to-end AI solutions including predictive models, GenAI/LLM systems, RAG pipelines, and agentic workflows. Own data preparation, feature engineering, evaluation, deployment, monitoring, and customer enablement. Build backend services and APIs, guide customers on model governance and responsible AI, and deliver workshops and reference architectures.

Support engineering teams by enabling AI code assistants, configuring development environments and IDEs, maintaining DevOps/DevSecOps and CI/CD pipelines, assisting with MCP integrations, implementing agentic workflows and automation, providing end‑user support and documentation, and collaborating with senior engineers to improve tooling and processes.

Lead design, training, and fine-tuning of large-scale ML/DL models (LLMs and generative systems) for drug discovery. Build scalable training pipelines, data pipelines, and production-ready model deployments; collaborate with engineering teams; translate research into applied AI solutions and continuously improve model performance and reproducibility.

Provide daily support and troubleshooting for AI code assistants and development environments, help configure DevOps/DevSecOps pipelines and MCP integrations, assist with agentic workflows and automation, create documentation and onboarding materials, and collaborate with senior engineers to improve tooling and developer experience.

Support engineering teams in adopting AI code assistants and IDE tooling, troubleshoot and optimize development environments, maintain DevOps/DevSecOps pipelines and MCP integrations, implement agentic AI workflows, provide end-user support and documentation, and collaborate to improve onboarding and developer productivity.

The role involves creating SEO, CRO, and GEO-optimized content for the Australian market, leveraging AI tools and ensuring high editorial quality for improved organic traffic and conversions.

Lead an AI-first transformation of procurement operations: assess Source-to-Pay maturity, design automation and LLM data governance, select and deploy S2P and CLM technologies, implement RPA/ML solutions, enable high-fidelity spend categorization and supplier compliance automation, and drive stakeholder integration and change management with IT and executive leadership.

The AI Deployment Engineer will guide clients in adopting OpenAI's coding tools, collaborating with engineering teams to design and implement AI-enhanced workflows, build demos, and contribute to the OpenAI community through technical content and insights.

The role involves building and integrating LLM-powered systems, requiring expertise in Python, agent frameworks, and modern API development.

Responsible for executing supplier strategy, managing full sales cycle, and enhancing customer satisfaction through relationship building and operational excellence.

Design and deliver enterprise AI solutions on SAP BTP: build/deploy ML models (AI Core/Launchpad), integrate Joule across SAP products, prototype AI use cases, create intelligent workflows with SAP Build Process Automation, define AI architecture, MLOps pipelines, and multi-cloud integration patterns aligned with Clean Core.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Join a remote team as a Lead Data Scientist focusing on building Generative AI applications. Responsibilities include developing applications, implementing pipelines, and performing model tuning.

As a Senior Full Stack Developer, you will design and build end-to-end features across backend and frontend using .NET and React, collaborate on system architecture, and integrate AI capabilities.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The AI Engineer will maintain and enhance AI services on the Sootra platform, optimizing pipelines, managing microservices, and developing feedback systems to improve AI performance.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.