Engineering Manager, AI
LawPay
AWSCloudPython
Principal Software Engineer, Personalization and Recommendation Systems
Hearst Health
full-time
Posted on:
Origin: • 🇺🇸 United States • New York
Visit company websiteSalary
💰 $190,000 - $230,000 per year
Job Level
Lead
Tech Stack
AWSMicroservicesPythonReact
About the role
- Architect and develop services for real-time personalization across content feeds, product recommendations, newsletters, and marketing technology funnels.
- Build robust APIs and infrastructure to support dynamic recommendation use cases on web, mobile, and email.
- Understand and architect end-to-end implementation of key recommendation features—from data ingestion to ranking logic and delivery.
- Ensure high standards of performance, security, and fault tolerance in production systems.
- Collaborate with ML and GenAI teams to evaluate the use of large language models for dynamic content ranking, summaries, or affinity prediction.
- Drive integration of semantic search and LLM-based personalization where appropriate, ensuring real-time responsiveness and system scalability.
- Lead experimentation on AI-powered recommendation enhancements (e.g., hybrid LLM and collaborative filtering approaches).
- Provide hands-on mentorship and technical direction to a blended team of full-time and contract engineers.
- Lead planning, scoping, and prioritization of engineering tasks in alignment with cross-functional goals.
- Ensure code quality, velocity, and accountability across distributed development efforts.
- Drive build-vs-buy assessments for recommendation infrastructure, experimentation platforms, and personalization tooling.
- Evaluate and integrate third-party solutions as needed for features such as product recommendation engines and customer data platforms.
- Contribute to long-term architectural blueprints for personalization across Hearst’s brands.
- Partner with Product, Data, and UX to define technical requirements that balance personalization sophistication with performance and privacy.
- Work closely with ML engineers to integrate trained models into live production flows and iterate based on real-time feedback.
- Collaborate with analytics and experimentation teams to validate and optimize recommendation impact.
Requirements
- 10+ years in software engineering, with a focus on backend systems, personalization, or e-commerce platforms.
- Hands-on development expertise in Python, React, and building microservices at scale.
- Deep knowledge of recommendation systems: collaborative filtering, ranking algorithms, content-based and hybrid models.
- Demonstrated ability to lead hybrid teams and manage contract/vendor developers toward shared goals.
- Preferred: Experience delivering both content and product recommendation engines in production environments.
- Preferred: Experience deploying or integrating large language models (LLMs) into consumer-facing personalization or recommendation flows.
- Preferred: Experience working with AI model ops platforms (e.g., Vertex AI, AWS Bedrock).
