Principal Software Engineer

Job Title: Principal Software Engineer

Location: San Francisco Bay Area

Job Type: Open to remote for highly experienced candidates (6+ years minimum)

Summary:

My client is a biotech startup leveraging AI/ML technologies to develop precision cancer therapeutics. We are seeking a seasoned and talented engineer to join our team in a generalist fullstack engineering role, with a strong focus on backend development. The ideal candidate will have extensive experience building and leading end-to-end solutions in a collaborative, fast-paced environment. This individual will work closely with multiple teams, including laboratory and computational biology teams, data science, and ML teams to design and build scalable systems. The role includes working on a variety of projects, such as imagery processing pipelines, datalake design optimization, and integration with lab equipment.

Key projects may include (but are not limited to):

Developing new imagery processing pipelines

Improving and optimizing existing datalake infrastructure

Building integrations with a variety of lab equipment

Designing and implementing data observability and quality control systems

Supporting data pipelines and infrastructure

Key Responsibilities:

Collaborate with laboratory, computational biology, data science, and ML teams to design and build systems for observability, quality control, and data analysis.

Develop scalable tools for data exploration, analysis, and visualization.

Own and lead the design and implementation of data pipelines, from ingestion to processing and visualization.

Support and maintain the infrastructure required for large-scale data processing in the cloud.

Take responsibility for both technical architecture and project outcomes, with a focus on end-to-end ownership of solutions.

Communicate effectively with technical and non-technical stakeholders, ensuring all teams are aligned and informed throughout the project lifecycle.

Lead projects from ideation to production, making key technical decisions and taking ownership of the overall solution.

Work independently and demonstrate a proactive problem-solving mindset, taking initiative and owning your work.

Must Have:

5+ years of experience in software engineering (or 3-4 years with strong qualifications).

Strong experience with AWS (SageMaker experience is a plus).

Proficiency in Python.

Experience building and managing large-scale data pipelines in the cloud (AWS).

Strong experience in data ingestion and processing.

Experience designing and building production-grade software.

Ability to work across multiple teams in a highly collaborative environment, with excellent communication and interpersonal skills.

A problem-solving mindset and ability to work independently.

Experience owning the entire scope of a project, from infrastructure design to implementation

Strong desire to take ownership of technical decisions, with a focus on high-level solution design.

Comfort in working in an IC (Individual Contributor) role, with a desire to lead and own projects end-to-end.

A self-starter mentality, with the ability to independently lead projects and solve complex problems.

Nice to Have:

Experience with data lake technologies such as Spark, Ray, or Iceberg.

Familiarity with Kubernetes for container orchestration.

Experience with dbt.

Familiarity with Dagster for managing data pipelines.

Background or experience in biotech or scientific domains is a plus, but not a requirement.

Candidate Profile:

Years of Experience: At least 5+ years in the industry (3-4 years with strong qualifications can be considered).

Industry Expertise: Biotech or scientific experience is beneficial but not essential.

Experience working with internal data consumers (e.g., data scientists, research teams).

A self-starter with a problem-solving mindset.

Collaborative team player who thrives in a highly communicative environment.

Passionate about taking ownership of technical decisions and leading projects from start to finish.

A strong communicator, able to bridge technical and non-technical discussions effectively.