Top Artificial Intelligence Jobs in Delhi

Design and deploy AI-driven sales workflows that automate lead generation, qualification, outreach, and CRM orchestration. Integrate HubSpot, RingCentral, and middleware (n8n/Make/Zapier), build LLM-based agents and forecasting models, and document scalable playbooks to double lead handling without headcount increases.

Design, build, deploy, and optimize scalable AI-powered automations across sales, recruiting, and client success. Deliver 10-15 high-impact automations monthly, own the workflow lifecycle, monitor performance, and drive adoption while ensuring reliability, cost-efficiency, and documentation.

Contractor role to review and analyze U.S. tax statutes, Treasury Regulations, and the IRC; interpret complex tax provisions and identify nuances; summarize tax concepts into structured insights; provide feedback to improve AI-generated tax responses; and collaborate with AI development teams while staying current on legislative changes.

Design, build, and scale AI-powered marketing automation and orchestration systems integrating CRMs, marketing platforms, payment gateways, and analytics. Develop reusable deployment templates, automated testing frameworks, data architecture, and LLM/AI-agent driven workflows to optimize funnels and enable real-time performance tracking across multiple campaigns.

Evaluate and improve AI-generated tax analyses by reviewing legal and tax documentation, analyzing statutory language, identifying compliance issues, contributing to tax AI datasets, and providing structured feedback while monitoring U.S. tax law updates.

Build end-to-end infrastructure for AI agents: design React/TypeScript UIs, implement Python agent harnesses, develop Kubeflow-based MLOps pipelines, fine-tune foundation LLMs (LoRA/QLoRA/SFT/RLHF), deploy and operate services on Kubernetes, integrate agent frameworks, and apply software engineering best practices, testing, and CI/CD.

Design and implement production-grade AI agent harnesses, build and operate MLOps pipelines with Kubeflow, fine-tune foundation LLMs (LoRA/QLoRA, SFT, RLHF), deploy and manage services on Kubernetes, integrate agent frameworks, and apply software engineering best practices to move models from prototype to production.

Lead technical onboarding and go-live for mid-market/enterprise clients by designing and deploying AI agents, building WhatsApp Business API integrations, configuring CRM connections, advising on AI strategy, resolving complex post-launch issues, and enabling expansion through reusable integration assets.

Design and build end-to-end Generative AI features: implement Python-based LLM backends and orchestrations, integrate LLM APIs, create React frontends to surface AI outputs, and own prompt design, embedding pipelines, and deployment workflows.

Lead technical development of AI solutions for finance automation, mentor teams, integrate AI with enterprise systems, and present to executives.

As a Senior Agentic AI Lead, you will manage the agentic AI domain, engage with customers, oversee the AI lifecycle, and ensure effective data governance and analytics across various teams.

Assist in developing AI solutions for financial planning, working on projects involving data structures, algorithms, and integrating AI features into the platform.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

Lead a team of engineers to evolve the architecture and strategy of the AI Search platform, ensuring high-performance search systems meet strict operational metrics, while nurturing talent and fostering a collaborative culture.

The AI Operations Specialist will support CoinMarketCap's AI team by conducting feature evaluations, developing tools and automations, managing outreach, and collaborating with internal stakeholders to enhance AI operations.

The GTM Engineer will design and build automation systems for lead routing, pipeline management, and data syncing across various tools to enhance sales productivity and revenue growth.

Manage AI/ML projects from initiation to completion, ensuring alignment with goals and standards. Lead cross-functional teams, track project metrics, and oversee stakeholder communication and vendor management.

The role involves managing AI/ML project lifecycles, aligning with IT governance, and leading cross-functional teams to ensure project goals are met within budget and schedule.

Design and operate large-scale GPU infrastructure for distributed AI training, ensuring reliability, performance, and efficient customer partnerships.

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

The Site Reliability Engineer will provision and manage Kubernetes clusters, build automation tools, debug customer issues, and improve infrastructure reliability.

Lead global quality engineering and testing practices for AI-driven SaaS products, enhance automation, and ensure high-quality releases through effective strategies and collaboration.

As a Forward Deployed Engineer, drive customer success through AI deployments, optimize systems for reliability, and collaborate with teams to enhance products.

The AI Product Manager will lead product discovery and strategy, prototype solutions using AI tools, perform competitive analysis, track product metrics, advocate for user experience, and collaborate with different teams.

This role involves preparing proposals, understanding client requirements, assisting in technical solution design, and supporting sales teams in AI/Data projects.