What are the responsibilities and job description for the AI Engineer position at VeridianTech?
Job Role AI Engineer
Location - Johns Creek, GA, 30097
Duration: Full time
Job Description:
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:
- Multi-agent collaboration
- RAG/Vector databases
- Autonomous task execution
- IAM/Secure service integration
- Agents interacting with client's APIs, data platforms, and operational systems
- MCP based tool integrations for internal systems
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
- Develop AI agents/chatbots with tool integration (APIs, databases, services)
- Build using ADK (Python required; Java or similar preferred)
- Create multi-step agent workflows (reasoning, orchestration, context handling)
- Rapidly prototype using Agent Studio / AI Studio (or equivalent)
- Convert POCs to production services on Google Cloud Platform (Cloud Run / GKE)
- Integrate with Vertex AI, BigQuery, enterprise systems
- Implement guardrails, access controls, and monitoring
- Optimize latency, cost, and reliability
Enterprise Integration
- Integrate agentic systems with client's:
- Google Cloud Platform data ecosystem (BigQuery, Pub/Sub, Cloud Run)
- APIs, microservices, and event-driven systems
- Identity, security, and governance frameworks
- Define standards for agent safety, guardrails, and responsible autonomy.
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.