Description

You will architect end-to-end agentic AI systems, defining agent design, orchestration, and enterprise integration. This role involves leading technical design reviews and mentoring junior engineers on AI system principles.

This role is on-site.

Responsibilities

• Design advanced agent patterns including hierarchical structures, multi-agent collaboration, and dynamic tool management.
• Build scalable prompt engineering pipelines and fine-tune LLMs for domain-specific use cases.
• Implement Retrieval-Augmented Generation (RAG) systems with advanced retrieval strategies and semantic search.
• Establish evaluation frameworks, benchmarking methodologies, and cost optimization strategies for agentic systems.
• Develop production-grade monitoring, observability, and error handling for AI systems operating at scale.

Required Skills

• 5+ years of hands-on experience in Machine Learning, AI/ML, and Agentic AI systems.
• Strong proficiency in Python and/or PySpark for AI/ML development.
• Expertise in LLMOps, prompt engineering, fine-tuning, and RAG architectures.
• Deep understanding of LLMs, semantic search, and AI orchestration frameworks.
• Experience building scalable, production-grade AI systems.
• Familiarity with cloud platforms Azure and GCP.
• Knowledge of CI/CD, observability, monitoring, and testing for AI systems.

Preferred Skills

• Experience with reasoning architectures incorporating planning, reflection, and self-correction mechanisms.
• Strong analytical, architectural, and problem-solving skills.

Key Skills

Education

Any Graduate