AIML Architect

Role & responsibilities

Experience range 1015 years.

Candidate should possess strong expertise in Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, Conversational AI, and Enterprise AI Architecture.

The ideal candidate should have hands-on experience with LLMs, RAG architectures, Agentic AI systems, NLP/NLU workflows, observability platforms, and enterprise-scale AI deployments.

Preferred candidate profile

Lead end-to-end AI/ML solution architecture and development for enterprise-scale applications.

Design and develop Conversational AI systems, virtual assistants, and intelligent Slackbots.

Build and optimize RAG pipelines and vector search systems.

Develop LLM-based solutions using prompt engineering and fine-tuning.

Implement Agentic AI systems and multi-agent workflows.

Work on AIOps use cases including anomaly detection and capacity prediction.

Collaborate with stakeholders to identify AI/ML opportunities.

Design scalable MLOps pipelines and observability systems.

Ensure AI governance, compliance, and security standards.