Lead AI Architect for Scalable GenAI & Multi-Cloud

Grid Dynamics; Porto; Presencial; EUR 120 000 - 180 000; Tempo integral

Resumo da oferta

Grid Dynamics seeks a senior AI architect in Porto to design and implement scalable generative AI solutions, including production-grade RAG and multi-agent systems. You will architect AI workloads on AWS and Azure, design data pipelines feeding LLMs, and contribute to core code with Python.

You will lead the deployment and optimization of LLMs, select tooling across Databricks, Snowflake, and cloud services, and guide teams on MLOps and LLMOps.

Qualificações

• Hands-on Python expertise with AI/ML libraries and API development.
• Experience deploying AI on AWS and Azure cloud services.
• Experience building autonomous multi-agent workflows with OpenAI Agents SDK.
• Expertise integrating Databricks and Snowflake for AI training/inference.
• Proven design and deployment of Retrieval-Augmented Generation (RAG) systems.

Responsabilidades

• Architect and implement robust generative AI solutions, including RAG architectures.
• Design AI workloads on cloud infrastructure using AWS and Azure.
• Design and optimize data architectures feeding LLM pipelines.
• Write production-grade Python code and contribute to core codebase.
• Select, fine-tune, deploy LLMs and optimize for production.
• Guide engineering teams on MLOps, LLMOps, and cloud choices.

Conhecimentos

Python programming

Async programming

API development

AI/ML libraries

MLOps / LLMOps

Ferramentas

AWS Bedrock

SageMaker

Azure OpenAI Service

Azure Machine Learning

Databricks

Snowflake

Descrição da oferta de emprego

Grid Dynamics seeks a senior AI architect in Porto to design and implement scalable generative AI solutions, including production-grade RAG and multi-agent systems. You will architect AI workloads on AWS and Azure, design data pipelines feeding LLMs, and contribute to core code with Python.

You will lead the deployment and optimization of LLMs, select tooling across Databricks, Snowflake, and cloud services, and guide teams on MLOps and LLMOps.