Must Have Technical/Functional Skills

Hands‑On Development & POCs
Python technology + Additional backend knowledge
Hands on Google Cloud Platform experience (Vertex AI preferred)
Implemented access control mechanism, trusted AI solutions
Strong SQL (Big Query preferred)
Experienced API building
Hands-on Experience ADK framework or similar agent framework
Hands-on Experience AI/LLM application or chatbots
Domain knowledge Supply chain / transportation domain experience (e.g., logistics, TMS, routing, shipment visibility)

Able to build rapid POCs demonstrating:

Develop reference implementations using:

Vertex AI Agent Builder
Agent Studio / AI Studio or rapid prototyping tools
Enterprise copilots or operational AI assistants
Gemini models
GPT‑based agents
Google Cloud Platform AI Agentic capabilities (If not, Azure AI Agentic capabilities is fine)
Create debugging, observability, and evaluation frameworks for agent behavior.

Roles & Responsibilities

Agentic AI Engineer

Enterprise Integration

Client Engagement & Sales Influence

Drive AI/Agentic use case discovery with client’s business and technology leaders.
Shape proposals, solution narratives, and executive presentations.
Act as the primary AI/Agentic technical advisor for the client’s account.

Cross‑Functional Leadership

Partner with cloud, data engineering, product, and business teams to deliver cohesive solutions.
Mentor engineers on agentic patterns, tool integration, and modern AI development.

AI ENGINEER

Quick Overview