Sophisticated AI Specialist

4 days ago


Hubli, Karnataka, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Title: Sophisticated AI Specialist

As a key member of our team, you will play a vital role in the development and integration of cutting-edge AI technologies. Your primary focus will be on building sophisticated AI agents using various frameworks.

Key Responsibilities:
  • Design and develop AI agents that can learn and adapt to complex tasks and environments.
  • Integrate large language models (LLMs) with our systems, ensuring seamless communication and data exchange.
  • Develop modular, reusable components for agent orchestration and task automation.
Model Deployment & Infrastructure
  • Deploy models using Databricks and Azure ML, integrating with enterprise-grade systems.
  • Implement APIs, WebSockets, and event-driven architectures for real-time AI services.
  • Collaborate with platform teams to ensure scalable and secure deployments.
Development & Automation
  • Work with CI/CD pipelines using Jenkins to automate testing and deployment.
  • Use GitHub Copilot, Codeium, or similar tools to accelerate development.
  • Maintain high code quality and documentation standards using Git, Jira, and Confluence.

The ideal candidate should have a strong background in machine learning and artificial intelligence, with experience in building generative AI applications for enterprise environments.

Additionally, they should be proficient in Python and modern development practices, with hands-on experience with LLMs and prompt engineering.

Experience building AI agents using frameworks like Lang Graph, Crew, or PydanticAI is also highly desirable.

We are looking for a self-starter with a growth mindset and curiosity for emerging AI trends, who can work effectively in cross-functional teams and adapt to evolving priorities.

They should possess excellent analytical and problem-solving skills, as well as strong communication and collaboration abilities.

The successful candidate will have a deep understanding of workflows like RAG and be familiar with Databricks and cloud-native deployment strategies.

They should also have knowledge of REST APIs, WebSockets, and event-driven systems, as well as proficiency with using CI/CD tools (Jenkins) and version control (Git).

A comfort level with AI-augmented development tools for rapid prototyping is also necessary.


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