Senior Software Engineer, Personalization Services
About The Position
The Senior Software Engineer, Personalization Services is responsible for building and operating the backend APIs and services that deliver AI-driven personalization to Internet Brands’ products. This role focuses on transforming ML outputs—retrieval results, rankings, scores, and signals—into reliable, low-latency services that power personalized user experiences in production. You will work closely with machine learning engineers, product managers, and platform architects to support rapid experimentation while maintaining high standards for performance, reliability, and scalability across multiple brands.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- 5+ years of experience building backend services in production environments.
- API design and service-oriented architectures
- Backend development in one or more modern languages (e.g., Java, Kotlin, Go, Python, or similar)
- Distributed systems and cloud-based infrastructure
- Proven ability to design systems with performance, reliability, and scalability in mind.
Nice To Haves
- Experience building personalization, recommendation, or search services.
- Familiarity with ML model serving and inference pipelines.
- Experience supporting A/B testing and experimentation platforms.
- Knowledge of caching strategies, asynchronous processing, and message-driven systems.
- Experience working in multi-tenant or multi-brand environments.
Responsibilities
- Design, develop, and maintain backend APIs and orchestration services that deliver personalized recommendations and content.
- Build service layers that integrate retrieval, ranking, and ML model outputs into user-facing product experiences.
- Implement request orchestration, fallback logic, and business rules to ensure consistent personalization behavior.
- Apply GenAI to enhance personalization, through the use of AI Agents and Agent Memory.
- Optimize personalization services for low latency, high throughput, and reliability.
- Implement caching, timeout handling, and graceful degradation strategies.
- Monitor service health, performance metrics, and error rates in production.
- Ensure systems scale across high-traffic products and multiple brands.
- Partner with Product Management and Machine Learning teams to support rapid experimentation and A/B testing.
- Enable feature flags, model versioning, and configuration-driven experimentation.
- Support fast iteration cycles while maintaining production stability.
- Collaborate with Machine Learning Engineers to integrate models into serving environments.
- Work with the Principal Architect to align service design with platform architecture standards.
- Partner with Data Engineering to ensure upstream data and features meet serving requirements.
- Translate product requirements into robust technical implementations.
Benefits
- health insurance options such as medical, dental, and vision coverage
- flexible spending accounts (FSA) for medical and dependent care
- short-term and long-term disability insurance
- life and AD&D insurance
- 401(k) retirement savings plan with a company match
- paid time off (PTO)
- paid holidays
- commuter benefits
- access to our Employee Assistance Program (EAP) and well-being coaching services
- voluntary benefits such as home, auto and pet insurance, and discounted legal and financial services
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
1,001-5,000 employees
