Description

Architect and implement enterprise-scale AI, Machine Learning, and Generative AI solutions. You will own the end-to-end design, development, and deployment of LLM-powered applications and scalable ML pipelines.

This role is remote.

Responsibilities

• Design and implement LLM-powered applications using RAG, fine-tuning, embeddings, and AI agents.
• Develop scalable ML pipelines for model training, validation, deployment, and monitoring.
• Lead cloud-native AI solution design across AWS, Azure, or GCP.
• Integrate vector databases and implement MLOps best practices including CI/CD and model versioning.

Required Skills

• 10+ years of IT experience, with at least 5 years focused on AI/ML architecture.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Deep experience with Generative AI, LLMs, RAG architecture, embeddings, and prompt engineering.
• Hands-on cloud experience with AWS SageMaker, Azure ML, or GCP Vertex AI.
• Experience designing systems using REST APIs and Microservices.
• Familiarity with containerization technologies, specifically Docker and Kubernetes.
• Strong understanding of data engineering pipelines.

Preferred Skills

• Proven client-facing skills for technical discussions and requirement translation.

Key Skills

Education

Any Graduate