Top Artificial Intelligence Jobs in Delhi

Develop AI solutions in Voice AI, Computer Vision, and Conversational AI. Architect and build AI systems for monitoring, analytics, and customer support across EV infrastructure.

Design and implement AI-enabled ServiceNow solutions across ITSM, FSM, and ITAM. Provide technical leadership and ensure best practices in AI capabilities, facilitate stakeholder workshops, and guide project teams.

Senior Data & AI consultant responsible for designing, developing, and delivering cloud data and AI solutions on Microsoft platforms. Lead data engineering, platform modernization, ML readiness, MLOps, and Azure-based deployments while collaborating with customers and teams to drive adoption and technical excellence.

Lead WAIG's product function end-to-end for AI solutions in health, education, and agriculture. Define multi-year product vision and roadmap, ensure disciplined delivery from MVP to scale, build and mentor distributed product teams, engage governments and donors, and represent product capability in partnerships and fundraising.

Manage and design integration processes using Boomi and Workato, supporting and developing solutions for complex business issues. Mentor team members and ensure effective communication with stakeholders.

Manage early-stage grantmaking for the Transformative AI Fund: evaluate applications, recommend grants, source opportunities, support grantees, build partnerships, represent the fund, and develop systems and LLM-assisted tooling to improve grant processes.

Define and deliver AI agents for enterprise spend management. Own vision, architecture, and roadmap; design agent patterns, observability, and closed-loop training; partner with engineering, data science, UX, and go-to-market teams; engage Fortune 100 stakeholders to ship reliable, explainable agentic workflows for invoicing, vendor onboarding, contracts, dispute resolution, and cross-border payments.

Design, build, and deliver enterprise-grade Generative AI and AI/ML platform capabilities: reusable services, APIs, microservices, RAG and agentic solutions, model lifecycle tooling, inference and monitoring, event-driven streaming with Kafka, CI/CD and DevOps automation, and platform observability to accelerate AI adoption across business domains.

Lead and execute AI-driven consumer product initiatives for search, recommendations, personalization, and conversational experiences. Collaborate with engineering, design, data, and business teams to define requirements, use data and user feedback to refine products, and deliver improvements within the contract period.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

Lead the intelligent transformation of operations support functions through AI and data solutions, overseeing hands-on technical delivery and team leadership in AIOps initiatives.

Design, execute, and maintain test plans for an AI-powered platform. Perform functional, integration, regression, end-to-end, API, browser/device compatibility, and performance testing. Validate AI features, prompts, and generated responses; track and verify bug fixes; collaborate with developers and product teams; prepare launch-readiness reports and recommend stability and UX improvements.

Lead a team designing, delivering, and scaling AI and automation solutions across Azure and Microsoft 365. Manage hybrid identity, Azure operations, M365 administration, security/compliance, on-prem servers, vendor relations, and AI strategy (Copilot, OpenAI, Cognitive Services). Oversee governance, POCs, and enterprise adoption while providing L2/3 support and project delivery.

Design and build production AI systems for BJAK's AI Neobank: AI agents, LLM apps, RAG/retrieval, tool-calling, and automations for onboarding, KYC, risk, CRM and operations, with focus on accuracy, latency, cost, security, compliance and reliability.

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

The Solutions Engineer will partner with customers to help them derive business value from OpenAI's products, manage pre-sales processes, and provide technical expertise.

Technical pre-sales architect for enterprise AI engagements. Design end-to-end AI/ML infrastructures (GPU clusters, networking, storage, MLOps, inference), whiteboard architectures, validate NVIDIA integrations, collaborate with cloud and partner teams, drive proofs-of-concept via ATC, and ensure clean handoff to delivery while supporting revenue-generating sales efforts.

Design, implement, and lead large-scale generative AI and ML systems (LLM fine-tuning, RAG, agents, Graph ML). Build REST APIs, deploy with Docker/Kubernetes, optimize big-data workflows, mentor engineers, and operate ML services on cloud platforms.

Lead design and delivery of cloud-native, event-driven platforms and applications. Drive full lifecycle development, champion engineering best practices, implement production-ready solutions, and build AI/LLM capabilities like RAG, embeddings, and model CI/CD across multi-cloud environments.

Operate and improve AWS-hosted SaaS environments using DevOps, automation, and AI tools. Troubleshoot production issues, automate operational tasks, support on-call, administer Windows-based web hosting (.NET/IIS/SQL Server), build CI/CD and IaC (Terraform), enhance observability, and drive responsible AI-assisted engineering to reduce toil and increase reliability.

The AI Engineer will develop, implement, and maintain AI systems and algorithms, ensuring data quality and deploying models in production. They will collaborate with teams to build data pipelines and ensure AI solutions meet requirements.

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.

Create original graduate-to-PhD-level problems and rigorous step-by-step solutions in STEM fields, review AI-generated answers to identify reasoning or factual errors, and ensure clarity and verifiability. Work remotely and asynchronously through an online platform after identity verification and an initial assessment.

Execute fashion design briefs using Raspberry AI to produce flats, tech packs, colorways, prints, mood boards, and concept visuals. Translate creative direction into precise prompts, iterate on feedback, maintain brand-consistent quality, document workflows, flag platform issues, and partner with US Customer Success for intake and delivery under tight turnarounds.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.