Agentic AI Architect (GCP)

Tata Consultancy Services Limited

Atlanta, GA, United States

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Compensation

$130,000.0 - $150,000.0

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Agile Methodology Artificial Intelligence BigQuery Cloud Computing Data Cleansing Information Engineering Data Retrieval Github Python (Programming Language) Machine Learning Natural Language Processing Tensorflow

+14 more

Systems Architecture Google Cloud Feature Engineering Data Ingestion Pytorch Large Language Models Generative AI Scikit Learn Google Cloud Functions Virtual Agents Software Version Control Automation Anywhere Programming Languages Data Generation

Job description

Lead the design and development of an Agentic AI platform. Deep expertise in machine learning, system architecture, and AI agent frameworks to build scalable, autonomous systems.
Architect and implement core systems for agent-based AI workflows.
Design and deploy LLM-based pipelines, agent orchestration, and vector-based memory systems.
Develop and optimize ML models, pipelines, and orchestration logic.
Drive technical strategy, tooling, and infrastructure decisions. · Architect and implement agentic AI systems leveraging GCP services (Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc.).

Requirements

Do you have experience in Version control systems?, * Programming Languages: Proficiency in Python is essential.

Agentic AI: Expertise in LangChain/LangGraph, CrewAI, Semantic Kernel/Autogen and Open AI Agentic SDK
Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, and AutoML.
Generative AI: Hands-on experience with generative AI models, RAG (Retrieval Augmented Generation) architecture, and Natural Language Processing (NLP).
Cloud Platforms: Familiarity with Google Cloud Platform (GCP).
Data Engineering: Proficiency in data preprocessing and feature engineering.
Version Control: Experience with GitHub for version control.
Data Science Practices: Skills in building models, testing/validation, and deployment.
Collaboration: Experience working in an Agile framework.
RAG Architecture: Experience with data ingestion, data retrieval, and data generation using optimal methods such as hybrid search. Google Cloud Platform

Benefits & conditions

Pulled from the full job description

Pet insurance
Health insurance
Vision insurance
Dental insurance
Commuter assistance, * Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.