Top Artificial Intelligence Jobs in Hyderabad

The Applied AI Engineer will design and build agentic systems that automate insights into results, collaborating with teams to ensure systems are effective, reliable, and integrated with current AI tools.

The AI Integration Engineer designs and implements AI model integrations, ensuring seamless data access and performance optimization for autonomous agents across workflows.

Responsible for building high-performance data infrastructure for autonomous AI agents, including data pipelines, knowledge graphs, and real-time data processing.

The Lead AI QA Engineer will design intelligent test automation frameworks, mentor teams, oversee QA strategy, and implement AI-driven testing solutions.

The Product Manager role focuses on supporting dataset onboarding, collaborating with product managers and engineering teams, maintaining roadmaps, and synthesizing stakeholder feedback.

Build, deploy, and operate production AI platforms: productionize LLM/SLM APIs, fine-tune and serve Hugging Face models, containerize services, manage cloud deployments, CI/CD, monitoring, scaling, and cost optimization.

The Senior Python Developer will build automated Databricks environments for AI/ML workloads and develop a Python-based monitoring and alerting ecosystem for AWS resources.

Lead the AI strategy and transformation to improve customer experience. Drive product development, collaborate with global teams, and manage AI initiatives.

The AI Tech Lead will design, develop, and implement AI solutions, focusing on LLM and RAG systems, while collaborating with engineers and product managers to innovate and optimize AI workflows.

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

Lead a team for developing LLM and multimodal AI systems for healthcare. Ensure clinical safety, regulatory compliance, and effective deployment in telemedicine.

The engineer will build automation frameworks for Databricks, integrate AI capabilities, and develop deployment workflows in AWS.

The Solutions Engineer will develop AI agents, configure automations, lead technical onboarding for enterprise customers, and deliver BI reports to enhance customer success.

The AI Engineer will develop, deploy, and optimize machine learning models for environmental and industrial applications, focusing on real-time object detection and classification.

The Senior AI/ML Engineer will lead the development of enterprise AI solutions, owning architecture and delivery, mentoring engineers, and ensuring compliance with responsible AI practices.

Seeking a senior AI/ML engineer with 6+ years experience to design and scale AI/ML platforms, innovate, mentor, and solve complex data challenges.

The role involves delivering AI solutions, developing models, supporting Agile practices, collaborating with teams, and focusing on execution and delivery.

The Generative AI Tester will validate AI-driven features, ensure model reliability, and drive end-to-end testing workflows in enterprise applications.

The Data Engineer will design and maintain AI data pipelines, manage cloud data infrastructure, and ensure data quality for analytics and machine learning operations.

Assist in developing AI solutions for financial planning, working on projects involving data structures, algorithms, and integrating AI features into the platform.

Develop scalable chatbots and virtual assistants using conversational AI technologies, integrate NLP/NLU, and collaborate across teams. Optimize performance through testing and user interaction analysis, while following Microsoft Foundry methodologies.

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

The role involves designing and optimizing large-scale ML data pipelines, ensuring high-throughput data ingestion and processing, collaborating with teams on data workflows, and architecting GPU-based environments.

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.