Advanced AI Engineer

2 days ago

Ellore, Andhra Pradesh, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

As a pioneering AI/ML Engineer, you will play a pivotal role in crafting innovative solutions that bridge the gap between artificial intelligence and machine learning.


This is an exceptional opportunity to leverage your expertise in building cutting-edge AI agents using frameworks like LangGraph, Autogen, Crew, or PydanticAI. You will be at the forefront of designing and optimizing prompt engineering workflows for Large Language Models (LLMs), such as GPT, Claude, and LLaMA.


Your primary responsibility will be to develop modular, reusable components for agent orchestration and task automation. This will involve collaborating with cross-functional teams to ensure seamless integration with existing systems.

Model Deployment & Infrastructure


Deploying models using Databricks and Azure ML, integrating with enterprise-grade systems is key to this role. Additionally, you will implement APIs, WebSockets, and event-driven architectures for real-time AI services, ensuring scalability and security.

Development & Automation


You will work closely with CI/CD pipelines using Jenkins to automate testing and deployment, streamlining development processes. Furthermore, you will utilize GitHub Copilot, Windsurf, Codeium, or similar tools to accelerate development, while maintaining high code quality and documentation standards using Git, Jira, and Confluence.

Must-Have Skills:


• 3–5 years of experience working Machine Learning / Artificial Intelligent or related fields.


• 1+ years of experience building Generative AI Applications for enterprise, deep understanding of workflows like RAG.


• Strong proficiency in Python and modern development practices.


• Hands-on experience with LLMs and prompt engineering.


• Experience building AI agents using at least one of Lang Graph, Crew, or PydanticAI.


• Familiarity with Databricks and cloud-native deployment strategies.


• Understanding of REST APIs, WebSockets, and event-driven systems.


• Familiarity with SDLC best practices and agile methodologies.


• Proficiency with using CI/CD tools (Jenkins) and version control (Git).


• Comfortable using AI-augmented development tools for rapid prototyping.

Nice-to-Have Skills:


• Exposure to MLOps/LLMOps workflows and model monitoring.


• Knowledge of enterprise security, compliance, and governance in AI systems.


• Exposure to best practices for code and model lifecycle management.

Soft Skills & Mindset:


• Strong analytical and problem-solving skills.


• Excellent communication and collaboration abilities.


• Self-starter with a growth mindset and curiosity for emerging AI trends.


• Ability to work in cross-functional teams and adapt to evolving priorities.

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