Director of Engineering, Data & AI

The Data & AI team is the engine driving data-informed decisions and intelligent features across Bolt. We design, build, and operate the critical data infrastructure, machine learning platforms, and analytical systems that underpin our products and strategic initiatives. Our work directly impacts Bolt's ability to provide secure, personalized, and frictionless experiences for millions of shoppers and merchants.

We are seeking a visionary and experienced Director of Engineering, Data & AI to lead this crucial function. You are a leader with deep technical expertise in modern data engineering, analytics, and machine learning, coupled with a proven ability to build and scale high-performing teams. You thrive in ambiguity, love tackling complex technical challenges at scale, and are passionate about leveraging data to create tangible business value. If you're excited by the prospect of shaping the future of online identity and commerce through data, we want to hear from you!

Responsibilities:

1. Leadership & Team Management:
   • Lead, mentor, and grow a high-performing, cross-functional team of data engineers, machine learning engineers, and potentially analysts/data scientists.
   • Foster a culture of innovation, collaboration, technical excellence, and accountability within the team.
   • Manage performance, support career development, and champion diversity and inclusion.
   • Recruit top-tier engineering talent to scale the team effectively.
   • Effectively manage and develop technical leads and potentially first-level engineering managers within your organization.
2. Strategy & Vision:
   • Define, articulate, and drive the long-term technical vision and strategic roadmap for Bolt's data platform, ML infrastructure, and AI capabilities.
   • Partner closely with Product Management, Design, other Engineering leaders, and business stakeholders (e.g., Risk, Growth, Finance) to align data/AI initiatives with company objectives and user needs.
   • Stay abreast of industry trends and emerging technologies in the data and AI space, incorporating relevant advancements into the team's strategy.
3. Technical Execution & Architecture:
   • 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.
   • Champion robust monitoring, alerting, and operational excellence for all owned systems.
4. Cross-Functional Collaboration & Impact:
   • Build strong relationships and collaborate effectively with stakeholders across the organization to understand their data needs, gather requirements, and deliver impactful solutions.
   • Clearly communicate technical concepts, strategic plans, progress, and risks to both technical and non-technical audiences, including executive leadership.
   • Champion data governance, quality, and security best practices throughout the company.

Requirements:

• 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.
• 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.

Bonus Points:

• 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.
• Direct experience applying ML to areas relevant to Bolt, such as fraud detection, identity verification, risk modeling, or personalization in e-commerce/fintech.
• Experience with specific cloud platforms (e.g., GCP, AWS, Azure) and their data/ML services.
• Familiarity with compliance and privacy regulations related to data (e.g., GDPR, CCPA).