Senior Software Engineer at Zeta Global | JobsWithPay

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Design, develop, test, deploy, and maintain distributed applications, microservices, backend services, and data-processing components for the company’s 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 programming languages and application frameworks such as Java, Python, Ruby, Ruby on Rails, or comparable technologies.
Design, implement, document, and integrate APIs, including RESTful APIs, using technologies and frameworks such as FastAPI, Ruby on Rails, Spring, or comparable API- development frameworks.
Design, build, and optimize data-processing and extract, transform, and load 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 distributed event-streaming or messaging technologies.
Design and maintain application components that use relational and NoSQL databases.
Develop data models, queries, indexing strategies, caching mechanisms, and data-access functionality that support high-throughput and low-latency applications.
Deploy, operate, monitor, and scale applications in cloud-computing environments such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, or comparable cloud platforms.
Implement and maintain application observability, centralized logging, distributed tracing, alerting, search, analytics, and production-debugging capabilities using technologies such as the Elasticsearch, Logstash, and Kibana stack, Honeycomb, or comparable platforms.
Investigate production incidents, conduct root-cause analysis, identify application and system performance bottlenecks, and implement corrective and preventive improvements.
Apply AI-assisted and AI-first software-development practices to software design, code development, automated test generation, code review, technical documentation, software modernization, and incident analysis. Integrate generative-AI or large-language-model APIs into software applications where required by the product.
Implement production controls for model evaluation, output validation, application observability, failure handling, privacy, security, and guardrails for AI-generated output.
Proactively identify and address project risks, architectural limitations, product gaps, data-quality issues, and operational concerns. Ensure the timely delivery of high-quality product updates and features through technical design and code reviews as well as unit, integration and automated testing.
Research and implement cost-effective technical solutions.
Create and maintain functional and technical documentation concerning software architecture, APIs, database schemas, data pipelines, platform integrations, deployment procedures, production operations, and product features.
Review client implementations to verify that solutions are scalable, secure, compliant, optimized, and aligned with platform best practices