Senior Software Engineer
TetraScience
Senior Software Engineer
TetraScience
Cloud-native platform centralizing scientific data
TetraScience · San Mateo, United States (Hybrid) · — · Posted 2026-08-14
Workplace: hybrid
Department: Engineering
TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
We are seeking a highly skilled Senior .NET Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing and developing high-performance, scalable applications using C#, the .NET Framework, and TypeScript. The role involves implementing automated testing and leveraging GitHub Actions for CI/CD pipelines. The candidate should also be proficient in production debugging and possess excellent communication skills. Knowledge and experience with AWS cloud services are also essential.
What You Will Do
High-Performance, Distributed, and Scalable Application Design:
Architect, design, and maintain distributed applications, ensuring high performance, scalability, and security.
Full-Stack Development:
Develop backend services (primarily C#/.NET and TypeScript) and cloud APIs, as well as modern, responsive front-end applications using TypeScript/React.
Microservices Architecture:
Design and implement loosely coupled, independently deployable services using AWS services such as DynamoDB, RDS, SQS, Lambda, API Gateway, and others.
Automated Testing:
Create and maintain automated unit, integration, contract, and end-to-end tests across microservices and UI layers.
CI/CD Pipelines:
Use GitHub Actions to implement and maintain CI/CD pipelines for both backend services and front-end applications.
Production Debugging & Optimization:
Diagnose and resolve production issues in distributed systems, including service-to-service communication, CPU/memory/network bottlenecks, and AWS service performance.
Observability & Operational Excellence:
Instrument services using OpenTelemetry (or equivalent) to enable earlier fault detection, clearer alerting, and stronger operational visibility. Contribute to SLO definition and MTTR reduction efforts across the platform.
Collaboration & Communication:
Work closely with product managers, tech leads, and other engineers to deliver reliable, maintainable, and scalable solutions. Communicate technical decisions clearly to both technical and non-technical stakeholders.
Required Skills
Desirable Skills
Soft Skills Needed:
No visa sponsorship is available for this position
The salary range for this position is $170,000-$220,000 USD. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
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Cloud-native platform centralizing scientific data
TetraScience offers a cloud-based Scientific Data Cloud that helps biopharmaceutical teams collect, centralize, and harmonize scientific data from lab instruments, software, and apps. It connects data across R&D, QA/QC, and manufacturing so data workflows run faster and data is ready for AI/ML analyses. The platform is vendor-neutral and open, designed to work with any lab equipment or software, providing end-to-end data management across the biopharma value chain. Its goal is to improve scientific outcomes by turning scattered data into a unified, ready-to-use data foundation that accelerates data-driven discovery and production.
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