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Top Software Engineer Jobs in San Francisco, CA

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19 Days Ago
San Francisco, CA, USA
294 Employees
Entry level
294 Employees
Entry level
Fintech
As a Technical Account Manager at Plaid, you will act as the technical liaison for customers, assisting them in integrating Plaid's products, providing ongoing solutions consulting, and working closely with engineering and product teams to enhance customer experience.
19 Days Ago
San Francisco, CA, USA
84 Employees
Mid level
84 Employees
Mid level
Security
As a Senior Software Engineer in Infrastructure at Abnormal Security, you will own a core system of the email security infrastructure, provide technical guidance, mentor team members, and lead system architecture and improvements. You will also ensure system stability and uptime while preparing for significant scaling.
19 Days Ago
San Francisco, CA, USA
Remote
113 Employees
Senior level
113 Employees
Senior level
Marketing Tech
The Senior Software Engineer (Backend) will lead complex projects, set engineering standards, improve testing and monitoring, contribute to technical strategy and architecture, and manage APIs for easier collaboration. This role emphasizes building web applications, especially using NodeJS and relational databases, while also fostering teamwork and mentoring.

Featured Jobs

19 Days Ago
San Francisco, CA, USA
39 Employees
Senior level
39 Employees
Senior level
Big Data
The Senior DevOps Engineer will build tools and processes for the NetBase Quid product, enabling engineers to operate cloud infrastructure efficiently, automating tasks, and ensuring security practices. Responsibilities include supporting development environments, collaborating with product developers, and managing on-call duties.
19 Days Ago
San Francisco, CA, USA
467 Employees
Senior level
467 Employees
Senior level
Information Technology • Machine Learning • Software • Analytics
As a Principal Software Engineer at Invisible Technologies, you will lead teams or technical initiatives, oversee technical vision, and ensure mentorship. You will design deployment architectures, focusing on cloud and Kubernetes while addressing networking and security. You should be adept with infrastructure as code tools.
19 Days Ago
San Francisco, CA, USA
278 Employees
188K-274K Annually
Senior level
278 Employees
188K-274K Annually
Senior level
Information Technology • Consulting
The Lead Data Engineer will design and expand Nuna's Data Platform, establish best practices, mentor team members, and collaborate with data scientists to optimize workflows. This role entails hands-on development, managing complex data sources, and ensuring data governance while contributing to innovative projects in healthcare.
19 Days Ago
San Francisco, CA, USA
120K-190K Annually
Senior level
120K-190K Annually
Senior level
Aerospace
The Senior Geospatial Software Engineer will implement image processing algorithms, manage processing systems, build APIs for data access, and collaborate with teams on features and improvements for hyperspectral imagery processing.
19 Days Ago
San Francisco, CA, USA
64 Employees
Senior level
64 Employees
Senior level
Other
The PLC Programmer will program and commission automated machine systems and integrate stations. Responsibilities include working with PLC and HMI systems, particularly with Allen Bradley equipment, and may also involve KUKA robot programming.
20 Days Ago
San Francisco, CA, USA
31 Employees
Expert/Leader
31 Employees
Expert/Leader
Information Technology
The role involves leading a team in the architecture, design, and development of mobile and web solutions for healthcare. Responsibilities include overseeing full stack development, engaging with stakeholders, optimizing product infrastructure, and creating technical documentation while ensuring high performance and scalability of solutions.
20 Days Ago
San Francisco, CA, USA
Hybrid
13 Employees
170K-225K Annually
Senior level
13 Employees
170K-225K Annually
Senior level
Artificial Intelligence • Information Technology • Machine Learning
The Lead Data Engineer will develop and optimize data infrastructure, build scalable ETL pipelines, manage data warehouses and lakehouses, ensure data quality, and collaborate with data science teams to support ML model deployment.
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