Top Artificial Intelligence Jobs in Delhi

The AI Product Manager will focus on managing product strategy, development, and implementation in cybersecurity, enhancing user experience and leveraging AI capabilities.

The Mid/Senior AI Cinematic Video Editor will create narrative-driven video content using AI tools, manage production workflows, and ensure visual cohesion.

As a Senior AI Engineer, you'll design and build production AI systems for document processing and conversational AI on enterprise data, utilizing tools like Databricks and Azure.

Lead the intelligent transformation of operations support functions through AI and data solutions, overseeing hands-on technical delivery and team leadership in AIOps initiatives.

Lead the strategy and execution for AI platform services, collaborating with engineering and design teams to deliver automated customer outcomes within cybersecurity operations.

Lead WAIG's product function end-to-end for AI solutions in health, education, and agriculture. Define multi-year product vision and roadmap, ensure disciplined delivery from MVP to scale, build and mentor distributed product teams, engage governments and donors, and represent product capability in partnerships and fundraising.

Design and build production AI backend services, APIs, and data pipelines integrating LLMs and multimodal models; implement retrieval, context assembly, and grounded outputs; create evaluation and regression-testing frameworks; develop internal review tools and React operational UIs; ensure observability, monitoring, and scalable, cost-effective deployments. Own features end-to-end and collaborate with product and engineering stakeholders.

Evaluate Chinese multi-turn AI conversations for relevance, grounding, helpfulness, and personalization. Create scenarios, compare and rank responses, identify errors, and provide structured feedback following guidelines. Maintain data quality and use a personal Google account for evaluations.

Advance detection and measurement in AI systems: expand jailbreak/adversarial libraries; build bias, fairness, and hallucination evaluation methodologies; develop interpretability techniques; translate research into engineering specs and methodology docs; publish work and represent the company with customers, regulators, and at conferences.

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

The Software Development Engineer in Test (SDET) designs and maintains automation frameworks using Microsoft Playwright, integrates AI tools for test generation, and performs API testing while collaborating with a global team.

The Principal AI Systems Engineer will architect, build, and own AI systems, develop production-grade AI pipelines, and ensure reliability through evaluation and governance.

Design and own Python-based features for Arango's Contextual Data Platform. Build RAG data pipelines, integrate and deploy private and cloud LLMs, develop and optimize agentic workflows, and scale AI workloads on Kubernetes. Work with SQL/NoSQL and graph architectures, ensure comprehensive testing (unit/integration/e2e), and evaluate new AI innovations for production-grade, secure deployments.

Build and scale production-ready AI and multimodal systems, design integrations between LLMs/VLMs, tools and microservices, optimize prompts and inference costs, implement observability/testing, apply Responsible AI, translate ambiguous requirements into specs, and mentor engineers toward AI-first engineering practices.

As a Senior Software Engineer at Sophos, you'll design and manage AI-driven firewall systems, focusing on enhancing automation, security, and compliance while taking ownership of end-to-end distributed systems.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

The Senior Product Manager will drive AI-led innovation, define AI product strategy, ensure compliance with responsible AI principles, and collaborate across teams to deliver impactful AI features.

The AI Engineer will develop and deploy GenAI applications, serve as a technical advisor, and collaborate on strategic initiatives in AI at Databricks.

The AI Engineer will develop, implement, and maintain AI systems and algorithms, ensuring data quality and deploying models in production. They will collaborate with teams to build data pipelines and ensure AI solutions meet requirements.

Build and maintain BigQuery data pipelines, map warehouse schemas, and craft SQL to feed LLMs. Develop Claude Skills and Gemini Gems, collaborate on prompts, validate AI outputs, and design AI agents to automate eCommerce analytics and operational workflows.

Annotate and review multimedia data (video, images, metadata) using detailed labeling guidelines; perform self-QA, participate in calibration, track issues, support quality workflows, and coordinate with stakeholders to meet throughput and quality targets.

Lead architecture and hands-on delivery of production agentic AI solutions: design reusable accelerators, integrate LLMs and retrieval (RAG), ensure reliability, security, observability, and guardrails, collaborate with cross-functional teams, mentor engineers, and contribute IP, patterns, and production best practices across clients.

Design, build, and scale no-code/low-code automation workflows and AI agents across business functions. Analyze processes, integrate systems via APIs/webhooks, implement OpenAI/Claude-powered solutions, build decision and scoring frameworks, deliver client-facing automation projects, and produce documentation and reusable playbooks to improve operational efficiency.

Lead product strategy, roadmap, and market launch for agentic AI solutions. Collaborate cross-functionally to define requirements, validate features, integrate with ServiceNow, drive POCs and production rollouts, and measure ROI and IP/services revenue.

Build and maintain merchant-facing payment products (onboarding, dashboards, checkout, transaction history). Develop payment APIs, integrate with banks/payment partners, design DB schemas for high-throughput transactions, use AI coding tools to accelerate development while validating AI-generated code, ship features end-to-end, and maintain production reliability.