Bolt is on a mission to democratize commerce by enabling frictionless shopping for retailers and shoppers. The company is seeking a Director of Engineering, Data & AI/ML to lead the development and scaling of data infrastructure and AI/ML systems that support secure, personalized, and frictionless commerce experiences.
Requirements
- Significant hands-on engineering background (typically 10+ years total experience) with demonstrated expertise in designing, building, and operating large-scale data systems.
- 5+ years of direct, hands-on experience and deep understanding of modern data stacks and concepts, including Data warehousing (e.g., Snowflake, BigQuery, Redshift), Data processing and streaming (e.g., Spark, Flink, Kafka, Airflow), Data modeling, ETL/ELT development, ML infrastructure (MLOps, feature stores, model serving, experimentation platforms), Business Intelligence and Analytics platforms.
- Proven ability to define technical strategy, develop multi-quarter roadmaps, and lead teams to execute successfully against them.
- Experience leading engineering teams in a fast-paced, high-growth technology environment (experience at venture-backed startups or established large-scale tech companies is highly relevant).
- Excellent communication, interpersonal, and stakeholder management skills, with the ability to influence and align diverse groups.
- Strong problem-solving skills and the ability to navigate ambiguity and make sound technical and strategic decisions.
- Experience with specific cloud platforms (e.g., GCP, AWS, Azure) and their data/ML services.
Responsibilities
- Lead, mentor, and grow a high-performing data team of AI/ML engineers and data scientists.
- Define, articulate, and drive the long-term technical vision and strategic roadmap for Bolt's data platform, ML infrastructure, and AI capabilities.
- Oversee the design, development, deployment, and operation of scalable, reliable, and cost-effective data pipelines, data warehouses/lakes, ML training/serving infrastructure, and analytics systems.
- Ensure architectural integrity, sound design principles, and adherence to best practices across all data and ML systems.
- Drive technical decision-making, balancing short-term delivery with long-term architectural health and scalability.
- Provide day-to-day technical guidance and oversight, ensuring high-quality execution and timely delivery.
- Build strong relationships and collaborate effectively with stakeholders across the organization to understand their data needs, gather requirements, and deliver impactful solutions.
Other
- BA/BS degree in a technical field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent practical experience.
- 7+ years of progressive engineering leadership experience, including at least 2+ years managing managers or senior technical leads.
- MS or PhD in Computer Science, Statistics, Machine Learning, or a related quantitative field.
- Experience leading distributed or hybrid engineering teams across multiple time zones.
- Familiarity with compliance and privacy regulations related to data (e.g., GDPR, CCPA).
