TetraScience

Lead Platform Engineer

Boston, Massachusetts, United States

Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Data ManagementIndustries

Requirements

The ideal candidate possesses over 10 years of hands-on experience in software and infrastructure engineering, with a proven track record of designing, building, and scaling distributed, cloud-native systems. Demonstrated experience as a technical leader or architect, making key decisions on system design, scalability, performance, and cost optimization is required. Strong proficiency in API-first design, including REST, GraphQL, and OpenAPI specifications, is essential. Proficiency in TypeScript and Python is also necessary.

Responsibilities

The Lead Platform Engineer will architect and evolve the cloud-native Tetra data platform to support high-throughput, low-latency data processing and customer-facing features. Responsibilities include designing scalable, distributed systems for authentication, authorization, data lifecycle management, search, operational intelligence, and real-time event processing. The role involves proactively analyzing platform performance and scalability, identifying constraints, and defining growth strategies. Collaboration with engineering and product teams to deliver supporting infrastructure for new services and applications is key. Building and maintaining infrastructure-as-code for automated, standardized, and secure deployments, enhancing observability and monitoring, and championing best practices in distributed systems design, scalability, and performance optimization are also core duties.

Skills

Platform Engineering
Cloud-native architecture
Scalability
Distributed systems
Data platform
AI
Cost-efficiency
Performance optimization
Reliability

TetraScience

Cloud platform for scientific data management

About TetraScience

TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.

Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees

Benefits

Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements

Risks

Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.

Differentiation

TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.

Upsides

Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.

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