Job Description

Your experience includes…

• Scientific background in biology, chemistry, or a related life sciences discipline, with a strong understanding of biotech, pharmaceutical, or life sciences R&D workflows.
• Experience configuring or supporting an ELN, LIMS, registry, or scientific workflow platform (e.g., Benchling or comparable systems).
• Familiarity with scientific platform APIs, data warehouses, and integration patterns into downstream databases and analytics (e.g., the Benchling REST API and Data Warehouse).
• Data modeling skills, including designing and maintaining schemas and entity relationships and mapping them consistently across integrated scientific and engineering systems.
• Hands-on fluency with scientific data structures, metadata, sample tracking, assay workflows, and data capture.
• Experience using AI tools (or a demonstrated willingness and aptitude to learn them) and interest in applying AI to scientific and informatics workflows.
• Familiarity with AWS cloud services (e.g., S3, EC2, Lambda, and RDS) and how they support scientific data storage, integration, and compute workflows.
• Working proficiency in Python for scripting, data manipulation, and automating or integrating scientific systems and workflows.
• Strong analytical and problem-solving ability, exceptional attention to detail, and the judgment to work through ambiguous, cross-functional problems independently.
• Ability to work directly with scientists and translate experimental processes into system requirements.
• Strong cross-functional collaboration across wet lab, dry lab, software engineering, and computational biology.
• Strong documentation, communication, and prioritization skills.

It’s a bonus if you have…

• Hands-on experience with AI tools such as LLM-based assistants, AI coding tools, or AI-enabled scientific software.
• Familiarity with software engineering practices: version control (git), testing, release management, change control.
• Experience with genomics, sequencing, molecular biology, gene editing, or screening domains.
• Familiarity with BI tools and data visualization.

You are interested in…

• Owning hands-on configuration, support, and continuous improvement of our scientific software environment, including our ELN/registry platform (currently Benchling): registry, entities, requests, assays, results schemas, and metadata structures.
• Owning scientific data models and schemas, and ensuring they map consistently across the ELN and integrated scientific and engineering systems. Partnering with Software Engineering to integrate scientific data into downstream databases and analytics.
• Partnering with wet lab and dry lab teams to understand experimental processes, sample tracking, assay data capture, and sequencing workflows, and translating them into platform configuration.
• Supporting and enabling scientific AI tooling, helping scientists adopt AI capabilities within our scientific systems, providing training and guidance, and collecting feedback.
• Defining and enforcing scientific data capture standards, metadata consistency, workflow consistency, and change management for scientific systems.
• Providing user support, training, documentation, troubleshooting, and adoption support.
• Troubleshooting and solving problems directly, working through ambiguous issues across systems, data, and scientific workflows with rigor and attention to detail.
• Identifying opportunities to simplify workflows, reduce manual effort, and improve data quality.

What success looks like...

• Scientists have reliable, well-supported systems that reflect how R&D work is performed.
• Scientific systems are maintained, documented, and improved through clear, repeatable processes.
• Scientific data is captured consistently and is cleanly consumable by engineering and computational teams.
• AI tools are thoughtfully adopted and integrated into scientific workflows where they add real value.
• Scientific systems become less dependent on individual knowledge and more sustainable as team-owned platforms.

Growth opportunity...

This role is positioned to grow with the organization. As our R&D footprint, data infrastructure, and use of AI expand, there is clear opportunity to take on broader scope, deeper technical ownership, and increased leadership responsibility.

About you:

You are a scientifically minded systems expert who enjoys working at the intersection of research, technology, and innovation. You have experience supporting scientific software platforms and understand how R&D teams generate, manage, and use data throughout the research lifecycle. You are comfortable partnering directly with scientists, computational biologists, and software engineers to translate scientific workflows into effective system solutions.

As a hands-on member of the Research organization, you will own and continuously improve our scientific systems ecosystem, including electronic lab notebooks, sample and data management platforms, workflow enablement tools, and emerging AI-powered solutions. You are a strong problem solver who enjoys configuring systems, improving processes, and learning new technologies that help accelerate scientific discovery.

Meet your Manager:

All inquiries regarding the posted position should be directed to the Talent Partner (see below). Interested individuals must apply directly to be considered for the opening.

David Tefft – Senior Director of Software Engineering and Lab Automation

David Tefft is a senior engineering leader with more than 20 years of experience building software for biotech and clinical and manufacturing labs, specializing in LIMS, data platforms, and integrations for regulated environments. As Senior Director of Software Engineering and Lab Automation at Tessera Therapeutics, he leads the delivery of lab-facing software while partnering closely with wet-lab and automation teams. Across earlier roles at Gritstone Oncology, N-of-One, and Good Start Genetics, he built and led engineering, QA, and support teams of up to 20 people. He is known for aligning stakeholders across Lab Ops, Automation, Quality, and IT, and for translating complex scientific workflows into reliable products. David holds a B.S. in Biochemistry and Molecular Biology from the University of Massachusetts Amherst.

Meet your Talent Partner:

Ben Hoogheem – Senior Director, Head of Talent Management

As Head of Talent Management at Tessera Therapeutics, Ben leads Tessera’s talent strategy across talent acquisition, performance management, and talent mobility.

Ben began his career as an in vivo Pharmacologist, which gave him a lasting appreciation for the rigor, creativity, and collaboration that drive scientific discovery. That foundation continues to shape how he helps build organizations designed to enable science thrive.

Ben is focused on aligning exceptional people with bold science – creating the structure, clarity, and culture that empower teams to scale effectively and achieve meaningful impact.

Compensation:

The stated base salary range represents Tessera’s good-faith estimate for this role. Actual compensation will be determined based on a number of factors, including but not limited to individual qualifications, years of relevant experience, internal compensation alignment, and external market data.

Tessera offers a competitive package of base and incentive compensation as well as a comprehensive benefits program designed to support the health, wellness, and financial security of our employees and their families. Benefits currently include group medical, vision, and dental coverage; group life and disability insurance; a 401(k) plan with company contribution; tuition reimbursement; and more.

This position is also eligible for an annual incentive bonus and equity grants as part of Tessera’s total rewards program.

Per Year Salary Range: $167,000 - $200,000