Agentic AI - GCP - PAN INDIA

Exp: 5yrs to 15yrs

• Project description:

The system utilizes specialized LLM agentsorchestrated via an Agent Development Kit (ADK)to perform automated data retrieval, multi-step logical reasoning, and hypothesis validation. This platform integrates 'Human-in-the-Loop' protocols to ensure that autonomous actions remain aligned with organizational safety and accuracy standards, transforming how the enterprise interacts with complex data silos.

Role:

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.

Must-Have Skills

• 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.

Good-to-Have Skills

• Excellent problem-solving and analytical skills related to AI integration challenges
• specific to customer needs.
• Experience in A2A, MCP for multi agent interaction.
• CICD pipeline for Multi Agents framework
• Experience integrating LLMs with Knowledge Graphs
• Using a memory bank for agent to agent communication.

Qualifications and Prior Experience

4-6+ years of experience in AI development, preferably on Google Cloud Platform.

Experience on building Agents, using Google ADK.

Experience in developing and deploying AI Solutions within an agent-based framework/Application

Experience/Familiarity with Agile development.

Certifications and Trainings:

• Professional
• Machine Learning Engineer