My client is a product attributes platform that injects the language of the customer across the existing retail stack, accurately connecting shoppers with the relevant products they’re looking to buy. They drive 8-9 figure revenue uplift for retailers and brands by dramatically improving their on-site search conversion, relevant product recommendations, SEO/SEM, item set-up and demand forecasting.
They use robust AI and NLP technologies to analyze a retailer's product catalog, then inject customer-centric attributes across the breadth of their existing retail stack to drive immediate relevance and connect those products with the buying objectives of customers. 7 of the top 25 fashion retailers in the world already work with them to deliver millions in top- and bottom-line revenue impact
The company is a female-founded startup headquartered in Mountain View, CA and is backed by Canaan Partners, Conductive Ventures, Sorenson Capital, NEA, Fernbrook Management and Unshackled Ventures, among others.
They are looking for a Staff/Tech Lead Software Engineer, Product Intelligence to build the core foundation of their Product Discovery platform that enables brands and retailers to understand the cognitive attributes of customers online and the 'why' behind 'what they do' in the customer journey. This person will follow a player-coach model, spending 30% of their time on leadership tasks and 70% of their time on individual contributor work.
- Design and implement robust, large scale, low latency services in the core product discovery platform
- Work cross-functionally with Engineering leaders, product managers and ML scientists to build end-to-end solutions
- Champion best practices in design, coding, testing, monitoring and documentation
- Help in growing and mentoring the most awesome team
- 8+ years SaaS product development experience, preferably building data centric applications at scale
- Skilled in Java programming and familiarity with scripting languages such as Ruby, Python
- Deep understanding of microservice architectures, messaging/queuing systems, stream processing systems (like Kinesis, Kafka), Elastic Mapreduce, Elastic Search, NoSQL like mongoDB, DynamoDB
- Hands-on experience with cloud infrastructure such as AWS (preferred) or GCP, and container systems such as Docker
- Experience planning, prioritizing and leading large projects in a fast paced environment
Strong communication skills and ability to collaborate in an energetic cross-functional group
- BS/MS in Computer Science or equivalent
Nice to Have
- Experience working at a high growth SaaS startup
- Experience working in a ML stack
- Experience leading technical teams
- Experience driving business initiatives