Top Artificial Intelligence Jobs in Delhi

As a Staff Backend Engineer, you'll design backend architecture for AI governance, ensuring auditability and compliance, while collaborating with engineering teams to enhance product capabilities.

The Senior Backend Engineer for AI Governance will develop backend systems to support AI compliance, governance, and visibility for enterprise users, focusing on efficient architecture and implementation.

As an Intermediate Backend Engineer, you'll develop backend features for AI Governance, focusing on compliance tools, automated testing, and collaboration with cross-functional teams.

The role involves driving national revenue growth in enterprise sales, managing complex engagements, and building relationships with senior executives in the manufacturing sector.

The Senior SAP Basis Administrator oversees SAP implementations, administration, and database management while enhancing system performance and providing 24/7 client support.

Manage AI projects in Banking and Financial Services, focusing on agentic AI initiatives, data management, and digital transformation while employing Agile methodologies.

The Applied AI Engineer will design and build agentic systems that automate insights into results, collaborating with teams to ensure systems are effective, reliable, and integrated with current AI tools.

The Lead AI Engineer designs and delivers AI/ML and Generative AI solutions for banking platforms, integrating data and enabling AI-driven decisions.

The intern will contribute to research artifacts, conduct in-depth research, and assist with project management in emerging technologies.

The Systems Engineer will lead project delivery by providing technical guidance, ensuring best practices during deployment, and maintaining documentation, while also supporting customer success and continuous improvement efforts.

Develop and maintain full stack applications integrating AI models and financial datasets. Collaborate with teams to deliver secure, responsive web applications using modern technologies.

Lead the development of AI-powered customer support solutions, guiding a team to build scalable, reliable, and secure systems using LLMs and third-party integrations.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

Lead AI strategy and execution for content: research and prototype LLM and vision solutions, architect scalable AI pipelines to process millions of documents daily, manage production ML lifecycle (latency, prompt engineering, reliability), and mentor engineering teams to deliver mission-critical systems.

The AI Architect will design, develop, and deploy AI solutions, collaborating with teams to align architecture with business objectives, manage risks, and ensure compliance with security policies.

Lead product development for an insurance-focused SaaS solution, collaborating across multiple teams and ensuring compliance and quality of deliverables.

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

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.

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.

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

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.

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.

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.