Senior Software Engineer

Zeta Global•New York, NY

4d•Hybrid

About The Position

Zeta Global Corp seeks a Senior Software Engineer in New York City to design, develop, deploy, and own scalable distributed systems that support its customer relationship management and multichannel marketing technology platform. The role collaborates with software engineers, architects, product managers, and client-facing teams to define technical roadmaps and deliver platform capabilities that unify customer data across digital touchpoints and improve clients’ return on marketing investment. The engineer builds and maintains distributed applications, microservices, backend services, APIs, data-processing systems, and cloud-hosted applications. The role also applies AI-assisted software-development practices and, where required by products, integrates generative-AI or large-language-model APIs with appropriate production controls. The position may be performed remotely four days per week.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or Electrical and Computer Engineering.
At least 5 years of experience in the job offered or a similar occupation.
Experience developing production applications and services using Java, Python, Ruby, Ruby on Rails, or comparable technologies.
Experience with API development and integration, including RESTful APIs, using FastAPI, Ruby on Rails, Spring, or comparable frameworks.
Experience designing and optimizing high-volume data-processing and ETL pipelines.
Experience with Apache Kafka or comparable event-streaming or messaging technologies.
Experience with relational and NoSQL databases, data modeling, queries, indexing, caching, and data access.
Experience deploying, operating, monitoring, and scaling applications in cloud environments such as AWS, Azure, or Google Cloud Platform.
Experience with observability, logging, tracing, alerting, search, analytics, and production debugging technologies such as ELK or Honeycomb.
Ability to conduct incident investigations and root-cause analysis and address system performance issues.
Ability to apply AI-assisted development practices and implement production controls for AI-generated output.
Experience with technical design and code reviews and unit, integration, and automated testing.
Ability to create and maintain technical and functional documentation and review client implementations.

Responsibilities

Design, develop, test, deploy, maintain, and own distributed applications, microservices, backend services, and data-processing components for the marketing technology platform.
Analyze business and product requirements and translate them into scalable, reliable, and maintainable technical designs.
Develop and maintain production applications and services using Java, Python, Ruby, Ruby on Rails, or comparable technologies.
Design, implement, document, and integrate APIs, including RESTful APIs, using FastAPI, Ruby on Rails, Spring, or comparable frameworks.
Design, build, and optimize pipelines that ingest, validate, transform, enrich, and distribute high-volume customer and marketing data.
Develop and maintain event-driven and asynchronous data-processing systems using Apache Kafka or comparable technologies.
Design and maintain application components using relational and NoSQL databases; develop data models, queries, indexing strategies, caching mechanisms, and data-access functionality.
Deploy, operate, monitor, and scale applications in cloud-computing environments.
Implement and maintain observability, centralized logging, distributed tracing, alerting, search, analytics, and production-debugging capabilities.
Investigate production incidents, conduct root-cause analysis, identify performance bottlenecks, and implement corrective and preventive improvements.
Apply AI-assisted and AI-first practices to design, coding, automated test generation, code review, documentation, modernization, and incident analysis; integrate generative-AI or large-language-model APIs where required.
Implement production controls for AI model evaluation, output validation, observability, failure handling, privacy, security, and guardrails.
Identify and address project risks, architectural limitations, product gaps, data-quality issues, and operational concerns; support timely, high-quality delivery through technical design reviews, code reviews, and testing.
Research and implement cost-effective technical solutions.
Create and maintain functional and technical documentation covering architecture, APIs, database schemas, pipelines, integrations, deployments, operations, and product features.
Review client implementations to verify scalability, security, compliance, optimization, and alignment with platform best practices.