Head of Engineering

About Our Client: Our client is a frontier AI company building a next-generation AI platform - a generative AI + simulation-powered search engine. The Role: Lead end-to-end delivery of data engineering initiatives. Architect and scale the core data infrastructure that powers their business - from data lakes and enterprise data platforms to AI-enabled analytics products and agentic systems. High-impact opportunity to build foundational systems that drive decision-making across research, product, and commercial teams. Key Responsibilities Data Infrastructure & Architecture Design, build, and scale data pipelines and lakehouse architectures supporting enterprise, product, and commercial analytics at scale Own the data lake ecosystem, defining standards for ingestion, storage, transformation, and access across structured and unstructured data Evolve the data stack for scalability, performance, and developer experience, optimizing for multi-cloud compute and supercomputing environments Build and maintain centralized feature registry / feature store as single source of truth for feature cataloging, lineage, ownership, SLAs - ensuring training/serving consistency Data Products & Platforms Develop and own core data products including enterprise data platform, intelligence layer, and AI-powered analytics tools (including AI agents) for non-technical users Build robust data models supporting analytics, reporting, and ML across multiple business lines Enable Applied AI/ML Engineers (Agents) building agents that automate workflows Governance & Data Quality Champion data quality, governance, observability to ensure organization-wide trust in data Implement lineage and auditability for training data used in generative models Candidate Profile 12-15+ years designing and building data products - enterprise data platforms, analytics platforms, personalization systems in AI-native environments Hands-on lakehouse ecosystems, low-latency large-scale batch and streaming pipelines for ML optimized for GPU compute Feature stores, Spark/Ray/Dask, Databricks/Snowflake/Delta Lake/Iceberg Deep SQL, Spark, Python. Governance & observability tooling Translates complex technical concepts for product and commercial teams Scrappy startup experience - as technical as possible, as commercial as possible Originally posted on Himalayas