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Staff Software Engineer / Technical Lead

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Staff Software Engineer / Technical Lead

Tamarind Bio

Staff Software Engineer / Technical Lead

Skills

DynamoDBDockerAmazon EC2Machine LearningAIAWS

3 months ago

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Important information


Contract type:

Permanent

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

7 August 2026

What they need


About Tamarind Bio We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren’t feasible until now.

New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.

Staff Software Engineer / Technical Lead We're hiring a Staff Software Engineer to provide technical leadership across our engineering team as we continue to scale the platform behind Tamarind.

Today, our engineering team consists primarily of early and mid-career engineers. As the complexity of our systems and customer requirements continues to grow, we're looking for someone who can help guide technical decision-making, mentor engineers, and drive architectural discussions across the organization.

This is not an engineering management role.

We're looking for a hands-on technical leader who enjoys writing code, reviewing designs, solving difficult engineering problems, and helping other engineers grow. You'll work closely with the CTO to shape technical direction while remaining deeply involved in execution.

The role spans architecture, infrastructure, product development, code reviews, technical mentorship, and engineering best practices.

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.

The role requires someone who enjoys moving between architecture, implementation, operations, and mentorship while helping a growing engineering team tackle increasingly complex technical challenges.

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