Top Artificial Intelligence Jobs in Mumbai

Build and scale Snowflake-native AI execution layers and orchestrated agent workflows. Implement RAG, embedding pipelines, vector retrieval, context-routing, monitoring, and integrations with enterprise data using SQL, Python, and DBT. Ensure scalable, observable, and governed AI systems across the organization.

The role involves managing AI and ML projects, leveraging data analytics to provide services to diverse clients, and ensuring performance-based outcomes.

Seeking a Senior Data Scientist skilled in GenAI/LLMs to design and implement solutions for enterprise, conducting research and mentoring others.

The Network for AI Sales Specialist will develop and drive long-term sales strategies, support account managers, and engage with clients to sell complex solutions, establishing significant business relationships and meeting sales quotas.

As AI/Automation Ops Lead, ensure efficient operations of data pipelines, manage outages, oversee AI application performance, and mentor a team while maintaining 24/7 support.

The AI Engineer will design and develop cognitive data solutions using AI technology, manage data pipelines, and lead cross-functional teams to deliver scalable solutions.

The AI Platform Engineer will design and optimize AI/ML infrastructure, automate pipelines, and manage Kubernetes for effective machine learning model deployment and collaboration.

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.

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 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.

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