Staff Software Engineer / Technical Lead
Hands-on technical leader providing architecture guidance, mentoring engineers, and contributing to infrastructure, backend, APIs, and ML systems at an early-stage AI drug discovery startup.
About the job
What You'll Do
- Partner with the CTO on architecture, technical planning, and major engineering initiatives
- Provide technical guidance across a team of 7-8 engineers
- Lead design reviews and architectural discussions
- Help engineers navigate complex technical challenges
- Contribute directly to the codebase across infrastructure, backend services, APIs, and product development
- Review code and provide feedback on implementation approaches
- Identify opportunities to improve reliability, scalability, performance, and developer productivity
- Support technical decision-making across new products and platform capabilities
- Work closely with customers and internal stakeholders to understand requirements and translate them into practical solutions
- Help establish engineering standards as the team continues to grow
Week in the Life
- Collaborate with the CTO on technical priorities and architectural decisions
- Review designs and provide guidance on implementation approaches
- Build and operate services across infrastructure, ML systems, APIs, and customer-facing applications
- Participate in code reviews and technical discussions
- Help unblock engineers working through difficult technical problems
- Work directly with customers to understand requirements and gather feedback
- Balance hands-on engineering work with technical leadership responsibilities
Ideal Qualifications
- 7+ years of software engineering experience
- Experience serving as a senior technical contributor, staff engineer, principal engineer, or technical lead
- Strong software architecture and distributed systems experience
- Experience building and operating production infrastructure and cloud services
- AWS experience (EC2, S3, DynamoDB, Docker, etc.)
- Ability to mentor engineers and provide technical guidance across multiple projects
- Strong communication skills and sound engineering judgment
- Comfort operating in an early-stage startup environment
- Willingness to work onsite in San Francisco
Technology
- Our technology sits at the intersection of DevOps, MLOps, and Computational Biology
- We support workloads ranging from large-scale ML inference and model deployment to workflow orchestration across research, infrastructure, and scientific computing environments
Skills
AWS, EC2, S3, DynamoDB, Docker, Software Architecture, Distributed Systems, Infrastructure, Backend Services, APIs, MLOps, DevOps
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