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60 Trade Desk Software Engineer Jobs Hiring Near You

The Trade Desk

Software Engineer II

San Francisco, CA · On-site +1

$151K - $227K/yr

Software Engineer II Location: 425 Market Street, Suite 2400, San Francisco, CA 94105 ... Telecommuting permitted: work may be performed within normal commuting distance from The Trade Desk ...

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What is it like to work at Trade Desk?

Trade Desk is a dynamic and innovative company that prioritizes collaboration, creativity, and customer satisfaction, fostering a culture of open communication and mutual support among its employees.

The company's team structure is designed to encourage cross-functional collaboration, with employees working closely together to develop and implement cutting-edge advertising technology solutions. Trade Desk's offices are modern and well-equipped, providing a comfortable and productive work environment that supports employee well-being and growth.

Working at Trade Desk may appeal to candidates who are passionate about technology, innovation, and customer-centricity, as the company offers opportunities for professional growth, skill development, and contributions to the rapidly evolving digital advertising landscape.
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Infographic showing various Software Engineer job openings at Trade Desk in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution.
Software Engineer II

Software Engineer II

The Trade Desk

San Francisco, CA • On-site, Remote

$151K - $227K/yr

Other

Posted 28 days ago

Job description

Job Title: Software Engineer II

Location:  425 Market Street, Suite 2400, San Francisco, CA 94105

*Telecommuting permitted: work may be performed within normal commuting distance from The Trade Desk, Inc. office in San Francisco, CA.

Job Duties: Design, develop, and maintain backend services and system components using object oriented languages such as Java, Scala, or Python, following internal coding standards and design guidelines. Design and implement data processing workflows using Apache Spark or other large-scale distributed data processing frameworks to support business analytics and product requirements. Develop high-performance and scalable data access layers, including implementing algorithms for efficient querying, caching strategies, and low-latency data retrieval. Implement and maintain cloud-native services deployed on container orchestration platforms (e.g. Kubernetes, ECS) and integrate with cloud infrastructure components (e.g. IAM policies, load balancers, service meshes). Design and validate API contracts, service interfaces, and cross-service communication patterns, including REST, RPC, or asynchronous messaging. Create and maintain CI/CD pipelines (e.g. Gitlab CI), including automated build processes, test execution, and controlled deployment workflows to ensure reliable software delivery. Instrument applications for observability by implementing metrics, structured logs, or distributed tracing to improve system transparency and operational insight. Investigate and resolve software defects or performance issues by analyzing logs, system metrics, and profiling results, collaborating with relevant teams as needed. Collaborate with product and engineering teams to convert business and functional requirements into technical specifications and system designs with clear performance and reliability goals.

Salary: $151,400 - $227,000/year

Job Requirements: Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering or related field. Position requires working knowledge of the following skills gained through coursework or experience: at least one programming language, including Java, Scala, or Python; container orchestration platforms, including Kubernetes, and containerization technologies, including Docker; designing and validating API contracts and service interfaces, including REST, RPC, or asynchronous messaging patterns; implementing CI/CD workflows, including Gitlab CI, and automate builds, testing and controlled deployments; observability practices, including metrics, structured logging, or distributed tracing instrumentation; and diagnosing and debugging software issues using logs, system metrics, or profiling tools.

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