Top Artificial Intelligence Jobs in Delhi

Design, build, and own AI-powered full-stack platforms and features from discovery through production. Embed AI into products and workflows, ensure reliability and security, support incidents, and mentor teammates.

The Technical Architect for AI/ML will define architecture for AI systems, mentor teams, and align strategies with business objectives, utilizing cloud-native tools and frameworks.

The Technical Lead will design and implement advanced AI systems, lead a team, drive the development of AI features, and ensure robust model performance through evaluations and optimizations.

The role involves developing AI-driven analytics solutions, collaborating with cross-functional teams, and ensuring high code quality in an agile setup.

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

Lead the Data and AI Engineering Studio, overseeing technical vision, mentoring teams, delivering solutions, and engaging in business development and innovation.

The Senior Systems Support Engineer will provide system support for SAAS and Linux applications, troubleshoot issues, mentor team members, and enhance system monitoring. Requires expertise in Azure and cloud technologies, with a focus on AI application support.

The Senior AI Engineer will lead the design and implementation of scalable AI solutions, manage MLOps pipelines, and collaborate with cross-functional teams to ensure operational excellence across AI platforms.

The AI Intern will assist in the integration, deployment, and operationalization of AI models, focusing on data engineering, backend development, and quality assurance while supporting documentation and knowledge transfer.

As an AI Engineer, you will design and implement AI-driven solutions using LLMs and traditional ML techniques, ensuring integration with enterprise platforms and optimizing user interfaces. Collaborate with teams to establish AI standards and manage the AI solution lifecycle in Agile environments.

The AI Engineer will build and optimize AI/ML models, integrate them with existing systems, manage model lifecycles, and ensure ethical AI practices.

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

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

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

Design, build, and productionize scalable AI/ML pipelines and models (including LLMs and Generative AI). Deploy and optimize models across cloud and edge, implement MLOps (CI/CD, versioning, monitoring), and collaborate with data scientists and engineering teams to deliver reliable, low-latency AI solutions.

The role involves designing and building AI solutions, integrating them with products, mentoring junior developers, and ensuring code performance across different technology stacks.

Lead and grow the AI Forward Deployed Engineering team at Databricks, manage AI/ML transformation for customers, and develop professional relationships with executive stakeholders.

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.

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.

The AI/ML Engineer II role involves developing AI solutions, managing product backlogs, integrating LLMs, and collaborating on automation projects while leading improvements in IT processes.

OpenGov seeks an Applied AI Engineer to design and maintain APIs and middleware that connect AI capabilities to applications, focusing on backend development and system integration for AI workflows.

The QA Analyst will perform manual testing, create test cases, utilize AI tools, assist with automation, and collaborate with teams.

The ServiceNow Solution Architect - AI role involves leading and mentoring a team, designing and deploying AI-driven applications, managing application development, and integrating solutions into ServiceNow modules. Responsibilities include coordinating with stakeholders, troubleshooting, and ensuring adherence to technical standards.

The Senior AI QA Engineer will oversee test planning, automation framework development, API testing, and ensure high-quality AI solutions. Responsibilities include end-to-end testing across AI/ML systems, collaboration with data and DevOps teams, and mentoring junior QA members.

The AI/ML Consultant will design and develop AI solutions for sustainability, collaborating with teams to deliver scalable models and proof of concepts while engaging with clients for successful implementation.