Role Overview

As the AI Engineer for the Enterprise AI team, you are responsible for designing, developing, and deploying AI including Generative AI and Agentic AI frameworks, to build intelligent and autonomous systems. You will work with different business to help build the solution using AI and Gen AI frameworks. You will also be involved in developing Data based applications and Dashboards that are critical for business which has high visibility.

Responsibilities

Design, build, deploy, and monitor AI/ML models, agents, and model endpoints for reliable production performance.
Develop Agentic AI and Generative AI solutions using prompt engineering, RAG, multimodal AI, and autonomous reasoning capabilities.
Integrate AI models into business applications and production environments, including applications deployed on Azure infrastructure.
Build and maintain data and MLOps pipelines using Snowflake, CI/CD practices, model versioning, artifact management, and release processes.
Collaborate with data scientists, software engineers, and product teams while creating BI dashboards in Power BI/Tableau and staying current with AI trends and best practices.

Requirements

Strong programming skills in Python, Java, or C#, with experience using AI libraries such as TensorFlow, PyTorch, and related frameworks.
Hands-on experience with Generative AI (e.g., LLMs), Agentic AI systems, and AI frameworks like LangChain, Hugging Face, or OpenAI APIs.
Basic understanding of cloud computing and cloud-based AI tools such as AWS SageMaker, GCP AI, and Azure ML.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
0–2 years of relevant AI/Data Engineering experience.

Skills

Python
LangChain
Generative AI
Azure
PyTorch

Nice to Have

Experience in real-time AI applications, Generative AI, or LLMs.
Knowledge of Agentic AI frameworks (AutoGPT, OpenAI's Assistants API, CrewAI).