Data Platform Architect (Azure, AWS)

Grid Dynamics; Województwo mazowieckie; On-site; PLN 300,000 - 520,000; Full time

Benefits offered by this job

Medical insurance

Sports benefits

Corporate events

Well-equipped office

Job summary

Grid Dynamics, a leading technology consulting and engineering firm, seeks a hands-on AI Architect to design, build, and deploy enterprise-grade Generative AI systems for Fortune 500 companies. You will bridge AI research with production software, leading technical strategy while personally building multi-agent systems and advanced RAG architectures on AWS and Azure.

Responsibilities include architecting scalable AI solutions, writing production-grade Python code, and guiding teams on MLOps,

Qualifications

• 10+ years of software/data/cloud experience with 3+ years delivering AI/ML in production
• Strong Python expertise with AI/ML libraries and API development
• Proven multi-cloud experience on Azure and AWS (Bedrock/SageMaker)
• Hands-on autonomous multi-agent workflows with OpenAI Agents SDK or similar
• Experience designing advanced RAG systems with vector stores and hybrid search
• Deep experience with Databricks and Snowflake for AI training/inference
• Excellent ability to explain complex AI concepts to engineers and executives

Responsibilities

• Architect and implement robust Gen AI solutions including production-grade RAG architectures
• Write production-quality Python code and contribute to core codebase
• Architect AI workloads across AWS and Azure, selecting appropriate services
• Design data architectures for LLM pipelines using enterprise data platforms
• Select, fine-tune, and deploy open-source and proprietary LLMs
• Lead engineering teams on AI engineering, MLOps, LLMOps and cloud infrastructure practices

Skills

Python

AI/ML

AWS

Azure

LLMOps

MLOps

Databricks

Snowflake

OpenAI Agents SDK

Pydantic AI

Education

Bachelor's or Master's in CS/Data Science/AI

Tools

OpenAI API

HuggingFace

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.

Min 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.

Would be a plus:

• 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
• 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.