AI Architect (Azure, AWS)

Grid Dynamics; Wrocław; On-site; PLN 240,000 - 420,000; Full time

Benefits offered by this job

Medical insurance

Sports

Corporate events

Professional development

Job summary

Grid Dynamics is seeking a hands-on AI Architect to design, build and deploy enterprise-grade Generative AI systems for Fortune 500 transformations. You will bridge AI research and production software, leading the technical strategy while personally building multi-agent systems, RAG architectures and AI data pipelines on AWS and Azure.

You will architect and implement scalable AI solutions, write production Python code, and guide engineering teams on AI engineering, MLOps, and cloud

Qualifications

• Bachelor’s or Master’s degree in CS/DS/AI or related field.
• Strong Python expertise with AI/ML libraries and API development.
• Experience deploying AI/ML solutions on Azure and AWS.
• Hands-on experience building autonomous multi-agent workflows.

Responsibilities

• Architect and implement robust Generative AI solutions, including production-grade RAG architectures and multi-agent systems.
• Write production-quality Python code, build prototypes and contribute to the core codebase alongside engineering teams.
• Architect AI workloads across AWS and Microsoft Azure, selecting services for each solution.
• Design data architectures for LLM pipelines with Databricks and Snowflake.
• Select, fine-tune, deploy and optimise open-source and proprietary LLMs.
• Guide engineering teams on AI engineering, MLOps, LLMOps and cloud infrastructure choices.

Skills

Python

Asynchronous programming

API development

Agent frameworks

Education

Bachelor's or Master’s in CS/DS/AI

Tools

AWS Bedrock

SageMaker

Azure OpenAI Service

Azure Machine Learning

Databricks

Snowflake

OpenAI Agents SDK

Pydantic AI

Job description

We are seeking a hands-on AI Architect to design, build and deploy enterprise-grade Generative AI systems for Fortune 500 enterprises undergoing digital transformation. In this role, you will bridge the gap between AI research and production-ready enterprise software, leading the technical strategy while personally building multi-agent systems, advanced RAG architectures and AI data pipelines on AWS and Microsoft Azure.

Responsibilities

• Architect & Implement: Design and implement robust, scalable and secure Generative AI solutions, including production-grade RAG architectures and multi-agent systems.
• Hands-on Development: Write production-quality Python code, build prototypes and contribute to the core codebase alongside engineering teams.
• Multi-Cloud AI Infrastructure: Architect AI workloads across AWS and Microsoft Azure, choosing the right services for each solution.
• Data Architecture for AI: Design and optimise data architectures that feed LLM pipelines, integrating enterprise data platforms such as Databricks and Snowflake.
• Model Deployment & Optimisation: Select, fine-tune, optimise and deploy open-source and proprietary Large Language Models.
• Technical Leadership: Guide engineering teams on best practices in AI engineering, MLOps, LLMOps and cloud infrastructure selection.

Requirements

• 10+ years of experience in software engineering, data engineering or cloud architecture, including 3+ years architecting and delivering AI/ML solutions in production, and a Bachelor’s or Master’s degree in Computer Science, Data Science, AI or a related quantitative field.
• Python Expertise: Exceptional Python skills, with deep familiarity with AI/ML libraries, asynchronous programming and API development.
• Multi-Cloud AI: Proven experience architecting and deploying AI solutions on both Azure and AWS (e.g. AWS Bedrock, SageMaker, Azure OpenAI Service, Azure Machine Learning).
• Agentic Frameworks: Hands-on experience building autonomous multi-agent workflows with the OpenAI Agents SDK, Pydantic AI or similar orchestrators.
• Advanced RAG: Proven track record of designing and deploying sophisticated RAG systems, including vector databases, advanced chunking strategies, hybrid search and reranking.
• Enterprise Data Platforms: Deep expertise in integrating, querying and managing data in Databricks and Snowflake for AI training and inference context.
• Consulting Mindset: Ability to explain complex AI concepts clearly to both engineering teams and executive stakeholders.

Nice to have

• Durable AI Agents: Experience building long-running, durable AI agents with Temporal.
• Conversational AI: Experience building, deploying and optimising enterprise chatbots and virtual assistants.
• Open-Source LLM Serving: Experience serving and optimising open-source models (e.g. Llama, Mistral) with vLLM, Hugging Face TGI or Ollama.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• 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.