Description

You will design and implement generative AI solutions, owning the end-to-end lifecycle from architecture to deployment.

This role is hybrid.

Responsibilities

• Design and deploy LLM-based applications using RAG and advanced prompting techniques.
• Build and manage the ML lifecycle using MLOps practices.
• Develop core AI services using Python and deep learning frameworks.
• Containerize and orchestrate models using Docker and Kubernetes.

Required Skills

• 10+ years of experience in software engineering or a related field.
• Expertise in Machine Learning and Natural Language Processing (NLP).
• Hands-on experience with LLMs, including RAG and Prompt Engineering.
• Proficiency in Python and PyTorch or TensorFlow.
• Experience with MLOps tooling and pipelines.
• Familiarity with orchestration tools like LangChain.
• Cloud experience with AWS or GCP.
• Containerization using Docker and Kubernetes.

Preferred Skills

• Experience with any Graduate degree equivalent in Computer Science or related technical field.
• Strong background in distributed systems architecture.

Key Skills

Education

Any Graduate