Top Artificial Intelligence Jobs in Delhi

Lead design and delivery of AI/GenAI solutions for telecom CSPs: prototype development, solution architecture, technology selection, integration, deployment planning, pre-sales support, and team mentoring to drive enterprise-scale AI adoption.

The Customer Segment Leader will manage a team, drive business development, establish senior-level connections, and deliver revenue targets, focusing on government clients in IT.

The Customer Segment Leader for the Government Sector will manage teams and drive business development while establishing senior connections to meet revenue goals and maintain excellent service delivery.

The candidate will lead a team, develop business strategies for government clients, drive revenue, and manage stakeholder engagement.

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.

Manage and grow an India-based AI Development team to deliver enterprise agent applications. Translate product priorities into sprints, partner with the Director of AI on roadmap and technical execution, establish async-first delivery rhythms across US/India, handle India operations (hiring, performance, compensation), coach on modern programming practices, and unblock work through cross-team relationships.

The Senior Data Scientist will architect real-time fraud detection systems, process large data sets, mentor teams, communicate findings, and innovate using AI technologies for effective risk management.

3–6 month internship supporting risk operations: monitor KRIs and case trends, assist investigations and case analysis, escalate findings, and help optimize AI/LLM tools, automation, and alerting workflows.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Lead data science efforts to design, develop, and productionize ML models, services and scalable data pipelines. Collaborate across lines of business to deliver AI-powered software solutions, perform analysis and insights, and optimize business outcomes in a secure, scalable financial-services environment.

Lead consulting engagements on technology policy, DPI, AI, and innovation ecosystems. Conduct research and policy analysis, manage stakeholder engagement, supervise analysts, deliver presentations, briefs and reports, support implementation of innovation programs, and develop proposals and thought leadership.

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

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

The Business Ecosystems Manager will support partnerships for industrial adoption of emerging technologies while driving digital transformation and managing stakeholder relationships.

Lead technology vision and architecture for enterprise projects; design cloud-native, data-driven and Generative AI solutions; ensure scalability, security, governance, and engineering excellence; run architecture reviews, POCs, and implementations; evaluate emerging technologies; influence clients via workshops and executive engagements; mentor architects and distributed engineering teams.

Lead AI opportunity discovery, prioritize use cases, design AI-enabled product strategies and implementation roadmaps. Translate operational challenges into feasible AI solutions, assess data readiness, define high-level architectures, build ROI models, develop governance for responsible AI, and drive stakeholder engagement and field-based implementation (50–80% travel).

Lead field-based research to identify and prioritise high-impact, solvable AI use cases for MSMEs across textiles, electronics, and pharmaceuticals. Develop implementation-ready roadmaps, cost-benefit analyses, data and instrumentation requirements, governance frameworks, and deployment models. Engage stakeholders, validate feasibility with technology providers, translate insights into accessible outputs, and support dissemination and workshops. Spend majority of engagement in the field and collaborate closely with Athena's leadership and research teams.

Teach a Skool community to build and implement AI automations, agents, and workflows. Create tutorials, step-by-step guides, and live workshops; provide hands-on support for content creation, faceless YouTube channels, and business process automation; stay current with AI tools and strategies.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide clear, opinionated feedback, distinguish response quality levels, and help define best practices for AI-assisted developer workflows.

Select, develop, and promote high-quality computational and AI manuscripts; set editorial policy on open science; recruit and support external editors; commission reviews and commentary; attend conferences and institutional visits; and curate published work for press and special projects to broaden the journal's impact.

Lead architecture and solutioning for enterprise-grade, AI-enabled, cloud-native applications. Collaborate with clients, create feasibility assessments and POCs, ensure scalable, secure platforms, and mentor delivery teams while representing the company in client meetings.

Lead development of agentic workflows and LLM systems, build LLM evaluation/tracing and prompt operations pipelines, integrate MCP-based systems, deploy and scale enterprise-grade AI/ML solutions, and collaborate with product and engineering teams.