AI Architect (Azure, AWS)

Essential functions

• 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.

Qualifications

• 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
• 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.