Lead Engineer, Audience Data Platform

Role

Lead engineering for the Audience Targeting and Contextual Intelligence Platform, owning one or more applications in the ecosystem and driving design and implementation of scalable backend services, data pipelines, API architectures, and real-time streaming workflows. This is a full-stack role that partners with frontend engineers, data scientists, product managers, and platform teams to deliver AI-enabled advertising technology and audience insights.

Key Responsibilities

• Design and implement 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 applications (Quart/FastAPI) integrated with PostgreSQL, Redis, and event-driven architectures (AWS SNS/SQS).
• Collaborate with frontend engineers on full-stack development using React and modern web frameworks.
• Integrate with core platform services for identity, metadata, and analytics to ensure interoperability.
• Design and manage multi-cloud infrastructure, primarily AWS with GCP integrations for ML/data workflows.
• Implement CI/CD, testing, deployment pipelines, and observability using Datadog, Sentry, and similar tools.
• Use AI-assisted development tools (e.g., GitHub Copilot, Codex, Claude) to accelerate delivery and improve code quality.
• Partner with product and data science teams to evolve contextual AI and embedding models for privacy-safe targeting.

Requirements

• 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 cloud experience, 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 and testing.
• Strong communication and cross-functional collaboration skills.

Nice to Have

• Experience building and maintaining taxonomy management systems.
• Knowledge of contextual or audience targeting, ad-tech systems, or recommendation platforms.
• Understanding of privacy-safe advertising, first-party data frameworks, and data-compliance standards (GDPR, CCPA).
• Exposure to machine-learning workflows or AI-based personalization systems.
• Experience with GraphQL and Elasticsearch.
• Familiarity with observability stacks such as Datadog and Sentry.

Location & Work Arrangement

Hybrid role based in New York City, requiring approximately 4 days per week in-office.

Benefits

• Medical, dental, and vision insurance from Day 1.
• 401(k) plan with company match.
• Access to training programs, workshops, and industry events.
• Employee Resource Groups and programs supporting inclusion and belonging.
• Hybrid work arrangement to support work-life balance.

Compensation

• Base salary range: $168,000 - $204,000 (actual pay depends on experience, skills, and other factors).