Ai Architect

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

Responsibilities

• Architect & Implement: Design and implement robust, scalable, and secure Generative AI solutions, including production-grade RAG architectures and multi-agent systems.
• Cloud Infrastructure Management: Architect AI workloads on cloud infrastructure, leveraging both AWS and Microsoft Azure services seamlessly.
• Data Strategy & Engineering: Design and optimize data architectures tailored for AI, integrating enterprise data platforms to feed LLM pipelines.
• Hands-on Development: Write production-quality Python code, build prototypes, and actively contribute to the core codebase alongside engineering teams.
• Model Deployment & Optimization: Select, fine-tune, optimize, and deploy open-source and proprietary Large Language Models (LLMs) effectively.
• Technical Leadership: Guide engineering teams on best practices for AI engineering, MLOps, LLMOps, and cloud infrastructure selection.

Qualifications

• Hands-on Python Expertise: Exceptional programming skills in Python, including deep familiarity with AI/ML libraries, asynchronous programming, and API development.
• Multi-Cloud Proficiency: Proven experience architecting and deploying AI solutions on both Microsoft Azure and AWS (e.G., AWS Bedrock, SageMaker, Azure OpenAI Service, Azure Machine Learning).
• Agentic Frameworks: Hands-on experience building autonomous workflows using advanced multi-agent orchestrators, specifically the OpenAI Agents SDK, Pydantic and similar.
• Enterprise Data Platforms: Deep technical expertise in integrating, querying, and managing data specifically within Databricks and Snowflake for AI training and inference context.
• Advanced RAG Architectures: Proven track record of designing and deploying sophisticated Retrieval-Augmented Generation systems, including experience with vector databases, advanced chunking strategies, hybrid search, and reranking mechanisms.

Nice-to-Have

• Conversational AI: Experience building, deploying, and optimizing enterprise chatbots and virtual assistants is a major plus.
• Open-Source LLM Deployment: Experience serving and optimizing open-source models (e.G., Llama, Mistral) using frameworks like vLLM, Hugging Face TGI, or Ollama.
• Experience with Temporal: Experience creating long running durable AI agents using Temporal will be a major plus

About Us

Grid Dynamics is a leading provider of technology consulting, agile co-creation, and scalable engineering services for Fortune 500 enterprises undergoing digital transformation. We combine business acumen with cutting-edge engineering to help enterprises deploy AI at scale, modernize core platforms, and implement next-generation cloud architectures.