AI Architect – Retail / GenAI

Inabia-Software-; Duluth (GA); Hybrid; USD 114,000 - 125,000; Full time

Job summary

Zensar seeks an AI Architect – Retail / GenAI to architect and deliver enterprise AI/GenAI solutions in a Hybrid Duluth, GA environment. The candidate will lead design for scalable AI platforms, governance, and secure production systems with executive sponsorship.

Ideal candidates have 12+ years in IT and 5+ years in AI/ML architecture, with strong retail domain experience and hands-on experience across LLMs, RAG, NLP, and modern data engineering on GCP/Vertex AI.

Qualifications

• 12+ years of IT with 5+ years AI/ML Architecture
• Strong Retail domain experience – Mandatory
• Enterprise AI/GenAI architecture & production implementations
• LLMs, RAG, Agentic AI, NLP, ML/DL
• Python, SQL, Spark & modern data engineering
• GCP & Google Vertex AI
• Enterprise AI platforms
• MLOps – MLflow, Kubeflow, Databricks or equivalent
• Vector databases – Pinecone, Weaviate, ChromaDB or equivalent
• AI governance, responsible AI, security & model monitoring
• Strong architecture leadership and executive stakeholder management

Skills

AI/ML Architecture

Retail domain experience

LLMs & NLP

Python

SQL

Spark

GCP

Vertex AI

MLOps

Vector databases

Responsible AI governance

Executive stakeholder management

Tools

Kubeflow

MLflow

Databricks

Pinecone

Weaviate

ChromaDB

Job description

Role: AI Architect – Retail / GenAI

Client: Zensar

Location: -Duluth, GA – Hybrid (3 Days Onsite)

Rate: $55-$60/hr

Visa Category: H1B only (C2C allowed) (No GC and USC on this)

Experience: 12+ Years

Type: Full-Time & Contract

Joining: Short Notice Preferred

Key Skills

• 12+ years overall IT with5+ years AI/ML Architecture
• Strong Retail domain experience – Mandatory
• Enterprise AI/GenAI architecture & production implementations
• LLMs,RAG, Agentic AI, NLP, ML/DL
• Python, SQL, Spark & modern data engineering
• GCP & Google Vertex AI
• Enterprise AI platforms
• MLOps – MLflow, Kubeflow, Databricks or equivalent
• Vector databases – Pinecone, Weaviate, ChromaDB or equivalent
• AI governance, responsible AI, security & model monitoring
• Strong architecture leadership and executive stakeholder management