AI Architect

Grid Dynamics; Atlanta (GA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Medical insurance

Sports activities

Corporate social events

Well-equipped office

Job summary

Grid Dynamics is seeking an AI architect to design and implement end-to-end AI systems, combining training of models with integration of Agentic tools for autonomous operations.

You will lead multi-agent orchestration, model customization, and scalable RAG pipelines, leveraging PyTorch, Hugging Face, and vector databases on cloud platforms. Join a fast-moving team delivering enterprise AI solutions.

Qualifications

• Hands-on experience building production-grade LLM applications, autonomous agents, and tool integration layers.
• Practical knowledge of ML frameworks (PyTorch, Hugging Face) and parameter-efficient fine-tuning techniques.
• Experience with cloud-native deployments and vector databases for scalable AI systems.

Responsibilities

• Design Agentic AI workflows enabling autonomous task execution through enterprise APIs.
• Oversee model training and fine-tuning pipelines, including dataset curation and LoRA/QLoRA methods.
• Architect scalable RAG pipelines with vector databases for accurate context retrieval.

Skills

GenAI

LLM apps

Agent orchestration

Tool integration

Tools

PyTorch

Hugging Face

LangGraph

CrewAI

MCP

Pinecone

Qdrant

AWS

Azure

Job description

We are looking for AI architect who knows enough about training models as well as integrating Agentic tools together.

Requirements

• Hands-on GenAI Experience: Strong background building production-grade LLM applications, autonomous agents, and tool-integration layers.
• Model Customization Skills: Practical knowledge of machine learning frameworks (PyTorch, Hugging Face) and parameter-efficient fine-tuning techniques.
• Production Engineering & Cloud: Mastery of Python-based backend architectures, vector databases (e.g., Pinecone, Qdrant), and cloud-native deployments (AWS/Azure).

Responsibilities

• Design Agentic AI Workflows: Architect multi-agent orchestration frameworks (e.g., LangGraph, CrewAI, MCP) enabling AI systems to autonomously use tools and execute tasks via enterprise APIs.
• Oversee Model Training & Fine-Tuning: Establish strategy and pipelines for dataset curation and efficient model customization (e.g., LoRA/QLoRA) using open-source foundations.
• Architect Scalable Knowledge & RAG Pipelines: Design high-performance Retrieval-Augmented Generation (RAG) systems integrated with vector databases for accurate context retrieval.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Benefits package - medical insurance, sports
• Corporate social events
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.