Top Artificial Intelligence Jobs in Delhi

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.

Own and build production AI/LLM applications end-to-end: architect RAG and agentic systems, implement function/tool calling, optimise inference costs, run evaluation frameworks, deploy on Kubernetes, and integrate with third-party platforms while collaborating with product teams to improve quality, latency, and cost.

Lead the planning and execution of test strategies, develop automated test suites for UI and API, and mentor junior team members.

Build and ship native Android features in Kotlin and Jetpack Compose; integrate REST APIs; improve performance, crashes and memory; collaborate with product/design; use analytics and on-device AI (TensorFlow Lite) to enhance user journeys for insurance and financial services.

Design, build and ship native Android features for an AI-enabled neobank using Kotlin. Integrate backend APIs, improve performance and reliability, collaborate with product and design to simplify financial user journeys, and apply on-device ML where it improves UX.

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.

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.

The Applied AI Researcher will design experiments, train models, and build pipelines for a GenAI platform while contributing to research and deploying systems in production.

Responsible for leading end-to-end AI research projects, developing domain-specific models, mentorship, and optimizing research-to-production processes while collaborating across disciplines.

The Principal Applied AI Researcher will define and lead domain-specific model strategies, manage model lifecycle, mentor researchers, and influence platform decisions in AI research.

Develop and deploy production-grade Generative AI services using LLMs, RAG, embeddings and vector retrieval. Build APIs and microservices with FastAPI, integrate models and enterprise workflows, optimize model accuracy and latency, implement monitoring/logging/evaluation frameworks, and support cloud/Docker deployments.

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.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

The role involves reviewing AI-generated outputs, generating content, and ensuring cultural accuracy in various media formats. Attention to detail and analytical skills are essential.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The AI Manager will lead a global team in AI project delivery, manage AI roadmaps, oversee LLMOps pipelines, and engage with stakeholders while ensuring compliance and performance metrics are met.

The AI QA Specialist will design and execute test strategies for AI systems, validate model outputs, implement monitoring dashboards, and ensure compliance with safety standards.

Design and implement production-grade AI models and algorithms, lead AI initiatives across organizations, enhance Agentic AI capabilities, and collaborate with teams to develop high-impact AI features.

The MDM Specialist will design and implement master data management solutions, integrate AI workflows, and ensure data governance and quality across customer and vendor domains.

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.

Develop and maintain AI systems for a financial platform, focusing on LLM pipelines, ML model serving, backend integration, and collaboration with engineering teams.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

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