ChatOps Gen AI Engineer

Responsibilities:

• Generative AI Development: Design and implement solutions leveraging Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG (Retrieval-Augmented Generation) setup.
• Machine Learning Model Implementation: Implement machine learning models using scikit-learn and TensorFlow.
• AI/ML Frameworks: Utilize Hugging Face, LangChain, LangGraph, and PyTorch for AI/ML development.
• Cloud AI Services: Work with cloud AI services, particularly AWS SageMaker and AWS Bedrock.
• MLOps & DevOps: Contribute to MLOps and DevOps practices, including data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes).
• API Development: Develop and maintain APIs following RESTful principles.
• System Integration: Integrate various systems using technical proficiency in Elastic, Python, YAML.

Required Skills:

• Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup.
• Ability to design and implement machine learning models using scikit-learn and TensorFlow.
• Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch.
• Proficiency with cloud AI services, particularly AWS SageMaker and AWS Bedrock.
• Knowledge of MLOps and DevOps practices, including data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes).
• Ability to develop and maintain APIs following RESTful principles.
• Technical proficiency in Elastic, Python, YAML, and system integrations.

Nice to Have:

• Proficiency with Observability tools, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python.
• Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.