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Senior Backend Engineer
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AI Summary
Lead the backend retrieval and ranking team behind recommendations at Raya, partnering with ML leadership to drive tech strategy. Own reliable, low-latency production systems, observability, and incident response while coaching a high-performing backend team. Requires 3+ years managing engineers and hands-on expertise in Go/Java, Postgres, AWS/GCP, and Kubernetes at scale.
Key Highlights
Lead backend recommender systems team at Raya
Own production systems, observability, and incident response
Partner with ML and Data Science on roadmaps and experimentation
3+ years managing engineers with hiring and performance responsibility
Expertise in Go/Java, Postgres, AWS/GCP, and Kubernetes
Key Responsibilities
Build, coach, and retain a high-performing backend team that specializes in recommender systems
Own reliable, low-latency production systems, observability, and incident response for recommendations
Create and execute a technical strategy grounded in product intuition and user empathy
Partner with the Machine Learning team to define roadmaps
Work with Data Science to co-own experimentation processes, tools, and best practices
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Technical Skills Required
Benefits & Perks
Comprehensive medical and dental coverage
$50 a day food delivery budget
Equity based employment
Unlimited vacation
12 weeks paid parental leave
$1,000 a year travel stipend
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Nice to Have
Experience with social networks or two-sided marketplaces in a subscription setting
Familiarity with how machine learning and AI fit into modern recommender systems
Experience with retrieval infrastructure such as Elasticsearch/OpenSearch, vector search, or feature stores
Job Description
Senior Engineering Manager, Recommender Systems
Raya - Remote Anywhere - Full-time
As Engineering Manager for Recommender Systems, you'll lead the team that builds the backend retrieval and ranking infrastructure behind recommendations at Raya. You'll partner closely with the head of ML to drive our tech strategy and ensure our members get the best experience possible on the core surface of our product.
We are looking for someone who is technically strong, has deep experience with production recommender systems, and has intuitive product-focused user empathy.
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