Bolt is on a mission to democratize commerce. We relentlessly prioritize our retailers—putting their brands front and center while enabling frictionless shopping at any touchpoint in the customer journey. At the center of it all is our rapidly growing universal shopper network—Bolt merchants such as Revolve, Luisa via Roma, Benefit Cosmetics, Kendra Scott, Lucky Brand Jeans, and Johnny Was can access tens of millions of shoppers, offering them a best-in-class checkout.
And revolutionizing ecommerce is only half of the equation—we’re also transforming the way we work. At Bolt, we have created a work environment where people learn to drive impact, take risks and make big bets, and grow from feedback, all while feeling welcomed and accepted for who they are. Come join us on the adventure today!
The Data & AI/ML Team is responsible for Bolt’s data architecture, agentic commerce, commerce data products (i.e. recommendations), Risk & Fraud, and 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/ML to lead this crucial function. You are a highly technical leader with deep expertise in modern data engineering, analytics, artificial intelligence, 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!
Please note that this is a contract-to-hire opportunity, with the option to convert to full-time after 3–6 months. The estimated compensation for the contract period is a flat monthly fee of $22,083–$23,750 USD (all-in, no benefits). Upon full-time conversion, the role will include RSUs and standard employee benefits.
Responsibilities:
- Leadership & Team Management:
- Lead, mentor, and grow a high-performing data team of AI/ML engineers and 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.
- 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.
- 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.
- 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).
Please download and explore the Bolt Super App prior to interview—our consumer experience is at the heart of everything we build!
- iOS
- Android
Check out our Engineering Blog!
#LI-Remote #BI-Remote
Benefits Upon Successful Conversion to Full Time Employee:
- Comprehensive health coverage: Medical, dental and vision
- Remote-first workplace
- Time away: Minimum of 20 days guaranteed PTO, paid holidays + floating holidays, your birthday off!
- Paid parental leave
- Competitive Pay
- Retirement plans
- Virtual and in-person team & company events
In addition to our core values, Bolt is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity and expression, genetic information, pregnancy and related conditions, veteran status or any other reason prohibited by law. On our mission to democratize commerce, the Bolt platform levels the playing field for everyone. As a company, we are committed to designing products, building a culture, and supporting a team that reflects the diverse population we serve (that is, everyone).
Top Skills
Similar Jobs
What you need to know about the Charlotte Tech Scene
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
