Responsibilities

• Design, develop, and operate scalable backend services for customer profile, consent, personalization, campaign, and marketing platform capabilities.
• Build data-intensive services that integrate with document or NoSQL databases, relational databases, caching layers, search platforms, object storage, and messaging, pub-sub, or event-driven systems.
• Develop clean APIs, service-to-service integrations, authentication patterns, error handling, logging, caching, and reusable platform libraries.
• Contribute to customer data platform workflows, including audience activation, downstream system synchronization, campaign metadata, tracking, and data observability.
• Partner with marketing, product, analytics, data engineering, and AI platform teams to translate business needs into reliable technical solutions.
• Modernize existing platforms across database models, identity systems, profile services, consent workflows, and operational tooling.
• Apply AI-assisted engineering practices while maintaining strong ownership of architecture, testing, security, code quality, and production readiness.
• Improve reliability through observability, alerting, automation, anomaly detection, and practical incident prevention.

Requirements

• BS in Computer Science, Engineering, or a related technical field, or equivalent experience.
• 8+ years of software engineering experience building backend services, APIs, data platforms, and production systems.
• Strong experience with one or more modern programming languages like Java, Python or Go, along with microservices architecture, and API design.
• Hands-on experience with document or NoSQL database design, indexing, migration patterns, performance tuning, and operational best practices.
• Experience with relational databases, SQL, distributed systems, cloud infrastructure, and containerized production environments.
• Experience building systems that move customer, behavioral, consent, campaign, or audience data across platforms with strong attention to data quality, governance, and reliability.
• Familiarity with caching, search, messaging, pub-sub, object storage, CI/CD, observability, and production operations.
• Experience using AI-assisted engineering workflows responsibly while maintaining ownership of design, correctness, testing, security, and production readiness.
• Self-motivated and collaborative, with the ability to own complex projects, drive progress independently, and communicate technical tradeoffs clearly across distributed teams.

Preferred

• Working knowledge of GDPR, PIPL, and related data privacy compliance and regulatory practices.
• Experience building or operating customer data platforms, identity resolution systems, customer 360/profile services, consent platforms, audience activation workflows, personalization engines, or marketing activation systems.
• Experience modernizing backend or data services that handle customer, audience, consent, or campaign data, including data model evolution, database migrations, and production cutovers.
• Strong understanding of reliable customer data activation, including data quality, governance, consent enforcement, synchronization, recovery, and downstream reconciliation.
• Experience applying AI or LLM-based systems to audience intelligence, personalization, campaign operations, content workflows, data discovery, or platform automation.

Benefits

• equity and benefits .