Principal ML/AI Architect

This role sits in the Data & AI practice and owns technical direction across several key European data and AI accounts at once. The work spans the full lifecycle of client programs: shaping target-state architecture for ML, GenAI and data platforms, leading discovery and pre-sales, and staying close enough to delivery to help teams solve hard engineering problems. Alongside client work, the role builds the practice’s reference architectures, playbooks and accelerators, and turns new ML/AI capabilities into reusable assets that lower implementation cost. Responsibilities
• Own target-state architecture and technical oversight for key European data and AI accounts: set direction, make and document key design decisions with account teams, and review designs and code.
• Help delivery teams resolve hard SQL and Spark problems hands-on.
• Lead consulting engagements, architecture assessments and discovery workshops.
• Lead technical pre-sales by contributing to RFP/RFI responses, solution proposals and estimates, and producing target architectures and delivery plans.
• Advise clients on data strategy and on data and AI/ML platform choices, recommend tools and methods that speed up their programs, and build the business case.
• Develop consulting methods, reference architectures, playbooks and reusable accelerators, make sure they are applied on live engagements, and mentor senior technologists.
• Track new ML/AI tools and vendor capabilities, turn them into reusable assets that reduce implementation cost, and work with marketing and sales to take these solutions to market.
• Work with the delivery organization to standardize the tools, technologies and processes that improve the quality, efficiency and cost of clients’ data platforms. Requirements
• Proven experience designing and delivering production ML and GenAI systems end to end, from data ingestion and feature pipelines through training, evaluation, deployment and monitoring, including ownership of architecture decisions and production operation.
• Deep expertise in either ML platforms and MLOps (MLflow, SageMaker, Azure ML, Databricks ML, model registry and serving, feature stores, drift monitoring) or GenAI and LLMOps (RAG, vector databases, agentic workflows, evaluation), with working command of the other.
• Strong hands-on experience with Azure and/or AWS ML and AI services and the data services that feed them.
• Project experience with at least two of Databricks, Snowflake and Microsoft Fabric as the data foundation for ML and AI workloads.
• Experience leading technical pre-sales: scoping, estimating and presenting solutions, and contributing to RFPs and proposals.
• Technical leadership across several client programs at the same time, including advising client leadership on data and AI strategy, trade-offs, cost and risk, and communicating clearly with engineers, business stakeholders and executives. Nice to have
• Working knowledge of the remaining specialization areas: data governance, quality and security (Unity Catalog, Purview, Collibra, GDPR); streaming (Kafka, Flink, Spark Structured Streaming, Kinesis, Event Hubs); knowledge graphs and ontologies; data mesh and data products.
• Data engineering foundations: SQL, Spark, ETL/ELT, CDC, lakehouse and medallion architecture, Delta Lake or Iceberg, enough to review code and diagnose hard problems with engineering teams.
• Enterprise data modeling experience.
• “Data for AI” experience, such as semantic layers, vector stores and governance for agentic workloads (willingness to learn is acceptable).
• Experience applying AI-assisted and agentic development practices, including agent harnesses, within delivery teams.
• Familiarity with Google Cloud ML and data services (e.g., Vertex AI).
• Domain knowledge in Finance, Retail/CPG, Manufacturing, Healthcare, Life Sciences, Energy or Travel.
• Experience leading teams of senior technologists in a consulting environment.
• Partner certifications (Databricks, Snowflake, Microsoft, AWS, Azure, GCP).

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.