Build and maintain backend services and RESTful APIs (Python/FastAPI/Django or Node.js); develop responsive React UIs; write SQL and manage relational schemas; deploy and operate cloud applications (AWS/Azure/GCP); build CI/CD pipelines; participate in code reviews, architecture discussions, troubleshooting, and cross-functional collaboration. Lead medium-sized data science projects and mentor junior team members.
What You’ll Do
Backend & API Development
- Build and maintain backend services using Python (FastAPI, Django) or Node.js
- Develop robust RESTful APIs and integrate with internal/external systems
- Improve performance, reliability, and scalability of backend services
Frontend Engineering
- Build intuitive, responsive UIs using React or similar frameworks
- Work closely with design and product teams to bring user experiences to life
Data & Databases
- Write efficient SQL queries and manage relational databases
- Support schema design, data modeling, and performance tuning
Cloud & DevOps
- Deploy and manage applications in cloud environments (AWS, Azure, or GCP)
- Build and maintain CI/CD pipelines (Jenkins, GitHub Actions, etc.)
- Use Atlassian tools (Jira, Bitbucket, Confluence) for workflow and documentation
Collaboration
- Participate in code reviews, sprint planning, and architecture discussions
- Work cross‑functionally with product, design, and QA
- Troubleshoot production issues and contribute to continuous improvement
What We’re Looking For
- 4–5 years of professional software engineering experience
- Strong experience with Python and frameworks like FastAPI or Django
- Solid SQL skills and experience with relational databases
- Hands‑on experience with React or similar frontend frameworks
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Experience with CI/CD, Jenkins, and Atlassian tools
- Strong understanding of engineering best practices and version control
Bonus Points
- Experience with Docker or Kubernetes
- Knowledge of microservices architecture
- Exposure to infrastructure‑as‑code tools (Terraform, CloudFormation)
Lead medium sized data science projects. Oversee data science standards and documentation. Mentor junior team members. Collaborate with other departments.
QualificationsGraduate in Data Science, Computer Science, Statistics, or a related field. 3-4 years of experience in data science or data analysis.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
