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Gen AI Engineer

Quantum Technologies

 

Falls Church, VA, USA

Posted On: 3 days ago
Experience: 5+ years
Availability: Remote
Openings: 2
Category: Gen AI Engineer
Tenure: No Preference/Any
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Description

MUST-HAVE SKILLS
Dialogflow CX – Mandatory
Conversational AI – Mandatory
Google Cloud / GCP
Gemini & Google Conversational AI ecosystem
Python / Software Development
Agentic AI & Multi-Agent Systems
RAG & Vector Databases
APIs & Enterprise Integrations
Production-grade AI deployments

You will work closely with strategic customers to solve complex challenges involving:
AI application development and agentic workflows
Multi-agent systems and MCP servers
Google Gemini-powered conversational solutions
Dialogflow CX and enterprise Conversational AI
Customer Engagement Suite (CES)
Contact Center AI (CCAI)
Enterprise APIs and legacy integrations
Data readiness and state-management challenges
AI evaluation, observability, safety, accuracy and latency

REQUIRED QUALIFICATIONS
12+ years of overall professional experience
Bachelor's degree in Engineering, Computer Science or related field, or equivalent practical experience
5+ years of software development experience using Python or similar languages
Experience architecting AI systems on cloud platforms, especially GCP
Experience with structured and unstructured data pipelines
Hands-on experience with Vector Databases and RAG architectures
Experience taking production-grade AI solutions from concept through customer deployment
Experience leading technical discovery with enterprise customers
Hands-on experience with Google's Conversational AI ecosystem

CRITICAL REQUIREMENT
Dialogflow CX / Conversational AI experience is REQUIRED.
Candidates should have production-level experience with Google Enterprise CX technologies such as:
Dialogflow CX
CX Agent Studio
SCRAPI
Agent Assist
CCaaS
Google Conversational AI ecosystem

PREFERRED QUALIFICATIONS
Master's or PhD in AI, Computer Science or related technical discipline
Multi-agent systems using LangGraph, CrewAI, ADK or similar frameworks
ReAct, self-reflection and hierarchical delegation patterns
LLM-native metrics such as tokens/sec and cost-per-request
State-management optimization
Granular AI tracing and observability
 

Education

Any Graduate

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