Top Artificial Intelligence Jobs in Mumbai

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 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.

As a Forward Deployed Engineer, drive customer success through AI deployments, optimize systems for reliability, and collaborate with teams to enhance products.

The Senior Product Manager - AI Platform will lead the development of AI infrastructure and enhance platform capabilities, ensuring efficient AI feature delivery and governance.

The Senior Product Manager - AI Growth will drive AI product adoption, engagement, and monetization, managing UI/UX, experimentation, and metrics for growth initiatives.

The role involves facilitating client workshops, mapping workflows, defining business metrics, and delivering AI-driven solutions. It requires strong communication skills and hands-on AI experience.

This role involves preparing proposals, understanding client requirements, assisting in technical solution design, and supporting sales teams in AI/Data projects.

Lead AI strategy and implementation for content processing at scale: research and prototype LLM and CV solutions, design robust, high-throughput AI services and pipelines, solve production ML challenges (latency, variance, observability), and mentor engineering teams to deliver mission-critical AI features.

The Senior Director Analyst develops insights on data management platforms, leads the research agenda, engages clients, and mentors junior analysts, utilizing extensive expertise in data management and AI solutions.

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.

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.

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.

Lead AI transformation engagements, overseeing client relationships and project delivery while mentoring consultants. Requires deep AI fluency and commercial instincts.

Create and edit brand videos using AI tools and traditional techniques. Collaborate with marketing and design teams, while staying updated on AI innovations.

The AI GTM Engineer will develop AI agents for go-to-market efforts, integrating with CRM and marketing tools to automate processes and enhance performance metrics for SDRs and AEs.

Lead enterprise clients to improve AI search visibility through analysis, custom GEO playbooks, C-suite presentations, prompt testing, monthly reporting, and cross-functional product collaboration to drive platform adoption and measurable visibility gains.

The role involves developing and implementing Machine Learning models, managing data pipelines, and supporting Data Science teams with best practices in ML operations and methodologies.

The role seeks an AI Lead to drive Generative AI and Computer Vision projects, focusing on precise visual transformations and model training while mentoring engineering teams in best practices.

The AI Lead will design, develop, and implement AI solutions to enhance the SDLC stages, mentor teams, and ensure responsible AI practices.

The AI Deployment Manager is responsible for post-sales training and enablement of OpenAI products, facilitating customer adoption through structured technical training, workshops, and ongoing support for AI product deployment.

The role involves collaborating with Data Science teams to implement and manage ML models, designing GenAI solutions, and automating ML operations, while establishing best practices in ML lifecycle management.

The AI/ML Engineer III translates business goals into ML metrics, leads ML model development, and oversees deployment and monitoring of AI solutions, driving innovation and collaboration across teams.

The AI/ML Engineer II will design, develop, and deploy scalable AI/ML solutions, optimize model performance, and integrate AI into products. The role requires collaboration with various teams and knowledge in deploying solutions to cloud environments.