Top Artificial Intelligence Jobs in Bangalore

As a Staff GTM AI Engineer, you'll lead the technical strategy for AI systems, architect scalable platforms, mentor engineers, and ensure the reliability of AI outputs while managing large-scale distributed systems.

The Engineering Manager will lead software engineering teams, drive AI adoption, oversee architecture for applications, and ensure delivery of impactful features while fostering a high-performing culture.

The Software Technologist role involves software development, coding, design, and proficiency in various technologies including Python and AWS. Candidates should have 5-8 years of experience and a passion for automation and collaboration.

Design and implement intelligent routing and inference orchestration for AI workloads, optimize system performance, and lead technical initiatives across teams.

The Senior Staff Developer will design and build security automation platforms, enhance SOC workflows, and lead architectural direction while mentoring engineers.

Lead design, develop, test and support SAP ABAP solutions, deliver RICEFW objects, integrate SAP with third-party systems, optimize performance, produce technical documentation, mentor junior developers, and help adopt AI/automation in the SAP ecosystem.

The Full Stack AI Engineer will develop AI products, build APIs, manage asynchronous job systems, and ensure secure software delivery for legal workflows.

Own production services, ensuring reliability and operational excellence while collaborating with teams to design and maintain a performant application platform. Responsibilities include managing SLIs, improving alert quality, and building automation scripts.

The Director of Software Engineering will lead teams in developing highly available distributed systems, focusing on payment processing, AI solutions, and innovative capabilities, while ensuring product quality and team engagement.

The Senior Quality Engineer will develop and enhance automated testing frameworks, focusing on AI-driven security solutions, ensuring performance and reliability of systems, and working with cloud environments and microservices architecture.

As a Quality Engineer 3 at Arctic Wolf, you will develop automated testing frameworks, ensure system reliability and performance, and enhance AI-driven security operations by validating AI/ML applications.

As a Quality Engineer 3, you will design and automate testing frameworks for AI/ML applications, ensure system reliability, and enhance CI/CD pipelines.

The Staff AI Platform Engineer will design scalable AI systems, improve reliability, mentor engineers, and collaborate on technical roadmaps, ensuring robust platforms and engineering excellence.

Lead the design and operation of AI-powered systems at scale, ensuring reliability and mentoring engineering teams while shaping technical architecture.

As a Forward Deployed Engineer, you will lead enterprise deployments by creating scalable solutions, integrating data systems, and operationalizing AI capabilities for complex customer requirements.

Responsible for developing AI-enabled applications for the AzurionEye platform, overseeing design and performance optimization, integrating components, and coaching team members in software best practices.

As a Senior Software Technologist, you will develop AI-enabled applications, enhance data services, optimize performance, and collaborate with cross-functional teams, ensuring quality in software development within healthcare systems.

The Software Test Engineer - AI Analyst develops test architecture for AI software, executes testing strategies, collaborates with teams, and ensures product quality.

The role involves developing Python-based storage and backup integrations, API services, debugging complex systems, and mentoring junior members while collaborating on technical solutions.

The Senior QA Engineer will work with development and Product Management to develop quality software, execute test cases, and improve testing processes.

Design, develop, and scale AI-enabling platform services and public APIs. Collaborate with teams to create AI solutions and ensure security.

The Software DevOps Engineer will develop, enhance, and implement software systems for generative AI, focusing on backend development, quality assurance, and scalability.

Develop methodology, flows, and tools for SoC and IP development efficiency; work with teams on automation tools using VLSI expertise.

As an AI Integrations Engineer, you'll build fullstack AI product features, integrate AI capabilities, and create user-friendly interfaces, focusing on real-world applications.

Develop scalable microservices for AI systems, focusing on APIs, data flows, and performance. Collaborate with teams to optimize AI-powered products and troubleshoot production environments.