AI Architect for enterprise AI

Grid Dynamics provides technology consulting, platform and product engineering, AI, and advanced analytics services. It helps enterprise companies undergoing business transformation solve technical challenges and achieve positive business outcomes. The company has extensive experience in enterprise AI and expertise in data, analytics, cloud and DevOps, application modernization, and customer experience.

• Design and implement robust, scalable, and secure 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 the right services for each solution
• Design and optimise data architectures for LLM pipelines, integrating enterprise data platforms such as Databricks and Snowflake
• Select, fine-tune, optimise, and deploy open-source and proprietary Large Language Models
• Guide engineering teams on best practices in AI engineering, MLOps, LLMOps, and cloud infrastructure selection

• 10+ Years of experience in software engineering, data engineering, or cloud architecture
• 3+ Years of experience architecting and delivering AI/ML solutions in production
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related quantitative field
• Exceptional Python skills and deep familiarity with AI/ML libraries, asynchronous programming, and API development
• Proven experience architecting and deploying AI solutions on both Azure and AWS, such as AWS Bedrock, SageMaker, Azure OpenAI Service, and Azure Machine Learning
• Hands-on experience building autonomous multi-agent workflows with the OpenAI Agents SDK, Pydantic AI, or similar orchestrators
• Proven track record of designing and deploying sophisticated RAG systems, including vector databases, advanced chunking strategies, hybrid search, and reranking
• Deep expertise in integrating, querying, and managing data in Databricks and Snowflake for AI training and inference context
• Ability to explain complex AI concepts clearly to engineering teams and executive stakeholders
• Будет плюсом: experience building long-running, durable AI agents with Temporal; experience building, deploying, and optimising enterprise chatbots and virtual assistants; experience serving and optimising open-source models such as Llama and Mistral with vLLM, Hugging Face TGI, or Ollama

• Competitive salary
• Flexible schedule
• Benefits package including medical insurance and sports
• Corporate social events
• Professional development opportunities
• Well-equipped office