Customer Support Engineer
VercelSalary not specified
Full Time
Junior (1 to 2 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Data Management, AIIndustries
Requirements
Candidates should have 7+ years of experience with a proven track record in performance, scale, resiliency, and customer support. Experience resolving technical support issues and escalations efficiently is required, along with troubleshooting experience with APIs and various integration types at scale in AWS. Proficiency with CloudNative platforms, microservices, Docker, SaaS deployments, and at least two of the following technologies: Databases, NoSQL, Kafka/Queueing Service, or Elastic Search is necessary. Experience in Python, PHP, JavaScript, React, Go, or Java, demonstrated experience debugging software reliability issues in distributed environments, excellent interpersonal and communication skills, self-drive, innovation, initiative, and familiarity with CRMs like Zendesk or Salesforce are also required. A Bachelor's degree in engineering or a related technical field is necessary.
Responsibilities
The Senior Software Engineer will work with customers to address technical issues, investigate end-to-end stability, scale, and performance problems reported by customers, and drive issues to resolution or identify workarounds. This role involves partnering with product and engineering teams, simulating customer issues in a lab environment to reproduce performance and scalability issues, and increasing product reliability. The engineer will manage the customer support to engineering escalation process, streamline communication with customer success, triage, extract, and document relevant information, and develop tools, scripts, benchmarks, and documentation to scale support efforts and reduce mean time to resolution.
Skills
Customer Engineering
Scientific Data
AI Cloud
Data Management
AI
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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