Job Summary

Agentic AI

Key Responsibilities

AI Engineer specializing in Agentic AI

Responsibilities

• Design and implement sophisticated Multi-Agent Systems (MAS) using frameworks
•  like the Agent Development Kit (ADK) to solve complex, multi-step reasoning tasks.
• Architect "Human-in-the-Loop" (HITL) workflows, ensuring seamless hand-offs between
•  autonomous agents and human subject matter experts for critical decision-making.
• Implement advanced reasoning patterns such as
• Chain-of-Thought (CoT),
• ReAct,
• and Self-Reflection
•  to improve the reliability and transparency of agentic outputs.
• Optimize long-context window utilization for analyzing vast datasets, ensuring
•  agents maintain coherence and accuracy when processing millions of tokens.
• Establish rigorous
• AI Evaluation (Eval)
•  frameworks to measure agent performance, including trajectory analysis, precision, recall, and faithfulness of reasoning.

Skill Requirements

• Solid understanding of Python programming 
• Experience in GCP projects and Vertex ai is must
• AI evaluation methods/metrics. ( like
• Precision, Recall, and F1 score
•  for agent trajectories and defect classification accuracy.)
• Experience with Agentic AI, managing sequential and loop-based workflows. specifically
•  using Google ADK or similar.
• Familiarity LLM Tuning (SFT, COT, ReAct)
• Experience in Data Analysis and process with multi agent architectures.
• Ability to debug and perform Root Cause Analysis (RCA) for issues.
• Ability to deploy agents. 
• Familiarity for implementing "Interrupt & Resume" patterns for human expert validation.
• Strong communication and teamwork skills, especially in the context of customer
•  collaboration.

Other Requirements