Lead Engineer, Audience Data Platform

Overview (Why This Role?)
We're looking for a Lead Engineer to help build and scale the next generation of our Audience Targeting and Contextual Intelligence Platform–a system that enables privacy-safe, contextually relevant advertising and deeper insights into audience engagement.

You’ll be the technical owner of one or more applications in this ecosystem, designing scalable backend services, building data pipelines, and integrating with Hearst’s core publishing platform. This is a full-stack engineering role where you’ll collaborate with dedicated frontend engineers, data scientists, and platform teams to deliver impactful, AI-enabled advertising technology.

About Hearst Magazines (Why Us?)
Hearst Magazines’ portfolio of more than 30 iconic brands in the U.S.—including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper’s BAZAAR, and Popular Mechanics — inspires, entertains, and builds new and bold experiences for an engaged and growing audience across digital, video, social and print, reaching nearly 130 million readers and site visitors each month. With sophisticated content creation, cutting-edge technology, and industry-leading data capabilities, we make media and products that move people across all platforms. We are a global media company that publishes nearly 200 magazine editions and 175 websites around the world—and together, we are shaping what’s next.

Key Responsibilities (What You Are Doing)

• Lead the design and implementation of backend services and pipelines supporting contextual and audience targeting, taxonomy creation, and data ingestion.
• Architect APIs, data models, and streaming workflows for real-time classification, recommendations, and audience insights.
• Build and maintain Python-based (Quart/FastAPI) applications integrated with PostgreSQL, Redis, and event-driven architectures (AWS SNS/SQS).
• Collaborate with and guide frontend engineers on full-stack development using React and modern web frameworks.
• Integrate with core platform services for identity, metadata, and analytics to ensure seamless interoperability.
• Design and manage multi-cloud infrastructure (primarily AWS, with GCP integrations for ML/data workflows).
• Implement robust CI/CD, testing, and deployment pipelines.
• Implement observability using Datadog, Sentry, and other monitoring tools.
• Use modern AI development tools (e.g., GitHub Copilot, Codex, Claude) to accelerate delivery and improve code quality.
• Partner with product managers and data scientists to evolve contextual AI and embedding models for privacy-safe, high-performance targeting.

Qualifications (What We’re Looking For)

• 8+ years of software engineering experience, with strong Python backend and full-stack development skills.
• 3–5 years leading technical design or architecture for scalable, data-intensive applications.
• Proficiency in PostgreSQL (including pgvector) and Redis for performance and caching.
• Hands-on experience cloud-based development, primarily AWS (S3, RDS, SNS/SQS, Lambda); exposure to GCP (Pub/Sub, BigQuery).
• Familiarity with Docker, Kubernetes, and modern CI/CD workflows.
• Comfortable using AI-assisted development tools for productivity, testing, and documentation.
• Excellent communication and cross-functional collaboration skills across technical and non-technical partners.
• Hybrid role based in NYC, with 4 days a week in-office.

Nice to Have

• Experience in building and maintaining taxonomy management systems.

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  Company

  Hearst

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