Description

You will architect and implement enterprise-scale AI and Generative AI solutions.

Responsibilities

• Architect end-to-end AI/ML and Generative AI solutions aligned with enterprise standards.
• Design and implement LLM-powered applications, including RAG, fine-tuning, embeddings, and AI agents.
• Develop scalable ML pipelines covering model training, validation, deployment, and monitoring.
• Lead cloud-native AI solution design across AWS, Azure, or GCP.
• Design vector database integrations and implement MLOps best practices like CI/CD and model versioning.

Required Skills

• 10+ years of IT experience, with 5+ years focused on AI/ML architecture.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, 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.
• Proven client-facing skills for technical discussions and requirement translation.

Key Skills

Education

Any Graduate