Top Artificial Intelligence Jobs in Bangalore

As an Engineering Intern, contribute to AI-driven projects using Java, Spring Boot, and various technologies while learning Agile processes and cloud-native development.

Lead cross-platform initiatives and technical projects, guiding teams and driving innovation in software delivery. Mentor engineers and ensure alignment with strategic goals.

Develop backend systems, focusing on Generative AI and machine learning for software delivery. Tasks include feature design, implementation, and collaboration with teams to enhance automation solutions.

The Senior QA Engineer will ensure quality in AI products, designing test plans for APIs, UI, and ML workflows, conducting performance testing, and collaborating with ML teams.

You will design and develop machine learning infrastructure and models, work with cross-functional teams, and build AI-driven applications, focusing on data scalability and performance.

The role involves designing and building scalable systems using Java, Python, and Angular, leading technical decisions, and improving CI/CD processes.

Lead multiple software engineering teams, drive technical strategy, manage software development lifecycle, promote innovation, and ensure compliance with best practices.

Guide technical evaluations and sales processes as a Solutions Architect, focusing on data engineering, AI, and big data solutions with Databricks.

The Sr. Solutions Engineer will advise on big data and AI solutions, lead client presentations, and support project integrations using Databricks.

The Gen AI Engineer is responsible for designing and developing AI agent workflows, leading code reviews, integrating with enterprise systems, and ensuring robust, secure implementations.

As a Principal QA Engineer, you'll ensure quality and security of AI services, design testing frameworks, and mentor junior testers in a collaborative Scrum team.

Design, build, and maintain scalable data pipelines for analysis using AI tools. Conduct analysis, optimize ETL processes, and create visualizations in Tableau.

The Senior DevOps Engineer will build and maintain backend infrastructure for AI data pipelines, support model training and production, and develop monitoring systems.

The Principal Core Services Engineer will develop AI-enabled cloud solutions, optimize core services, automate operations, and drive platform resilience in a multi-cloud environment.

The role involves managing AI integration and automation in the software development lifecycle, mentoring teams, and improving workflows through strategic leadership and collaboration.

Join the AI QA Assistant team to develop generative AI solutions for automating developer tasks. Responsibilities include backend development, integration with AI/cloud systems, and collaboration with product teams.

Design, implement, and optimize backend services and APIs for AI-driven features. Collaborate with AI and data teams to ensure high-quality backend solutions.

The Senior Software Engineer will bridge Applied Science and product teams, focusing on ML systems development and deployment, and AI platform services.

Lead development of observability products for AI and data workloads, optimize performance, and mentor engineers while building scalable data infrastructure.

The Senior QA Engineer will automate testing, validate AI model outputs, test API features, and collaborate across teams to ensure quality and performance.

As an AI Integration Engineer, you'll lead the deployment of ServiceNow and Workday connectors, troubleshoot integration issues, deliver customer workshops, and collaborate with product teams to enhance connector performance.

The role involves developing AI performance tools for large-scale systems, conducting performance studies, and automating performance analysis for optimization.

As an AI Process Automation Engineer, you will design and develop AI-driven automation tools, collaborate with teams to optimize processes, and create integrations and workflows using scripting and automation frameworks.

The AI Support Engineer provides customer support for DataRobot's AI platform, troubleshoots complex issues, collaborates with teams, and documents solutions.

Design and implement AI solutions, develop LLM-based applications, optimize retrieval pipelines, and maintain integrations while collaborating across teams.