Lead Platform Engineer (Search Platform) | TetraScience · Teeming.ai
TetraScience
TetraScience offers a Scientific Data and AI Cloud designed to liberate, unify, and transform raw scientific data into AI-native data. This platform aims to enable Scientific AI by providing a…
AI CloudChromatographyData ManagementData ReplatformingGxP ComplianceLab AutomationLife SciencesScientific Datatetrascience.com
TetraScience
TetraScience offers a Scientific Data and AI Cloud designed to liberate, unify, and transform raw scientific data into AI-native data. This platform aims to enable Scientific AI by providing a…
AI CloudChromatographyData ManagementData ReplatformingGxP ComplianceLab AutomationLife SciencesScientific Datatetrascience.com
HQBoston, US
Team Size182
Open Jobs39
Total Funding$99M
Latest Fundraise5 years ago
TL;DR
Company: TetraScience — scientific data and AI cloud for life‑sciences R&D
Headquarters / Founded: Boston; founded (original) 2014; rebuild noted from 2017; current founding year reported 2019 in one source
Product: Tetra Scientific Data and AI Cloud (Tetra OS) — vendor‑agnostic, AI‑native data platform
Recent round: Series B $80M announced April 15, 2021 (co‑led by Insight Partners and Alkeon Capital)
Used by many large pharma/biotech customers (company cites percent of top pharma customers)
Customers / traction:
Company Overview
Problem Domain
Scientific R&D data management and enabling AI for discovery and research productivity in life sciences.
Founded
2019
Industry
Software Development
Tech Stack
Cloud infrastructure / integrations
Instrument and informatics integrations
Funding Track Record
Series A- 2019-10-31
8,000,000
Series A included strategic investor Waters Corporation and investors Floodgate, First Round, Underscore VC, Founder Collective
Series B- 2021-04-15
80,000,000
Announced to accelerate rollout of the open R&D Data Cloud
Investor Signal
“Investors include Insight Partners, Alkeon Capital, Waters Corporation, Floodgate, First Round Capital, Underscore VC, Founder Collective, and others”
Founders
What we do
Join the Team
Lead Platform Engineer (Search Platform)
On-SiteUnited States {{REMOTE}}, US
On-Site • United States {{REMOTE}}, US
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We are seeking a Lead Software Engineer to help expand our scientific search platform beyond traditional keyword search and unlock new capabilities in chemical search, semantic search, and natural language search
In this role, you will work at the intersection of AI/ML, cheminformatics, knowledge representation, and distributed systems, enabling scientists to retrieve and reason over complex experimental datasets, chemical entities, assay results, and unstructured lab documents
As a technical leader of the Search Platform team, you will guide, design and implement new search capabilities while also owning the underlying infrastructure that powers them
Lead by example for building the systems, mentor engineers, and help shape the roadmap for search capabilities and platform evolution
This includes maintaining scalable, reliable services and continuously improving the platform as we expand our search offerings
You will collaborate closely with Applied AI Scientists, platform engineers, and product teams to deliver high performance search services that drive discovery, analysis, and decision making across the bio-pharma R&D lifecycle
Lead by example to architect and code the next-generation scientific search engine, building a system that can reason over billions of scientific data points—from chemical structures (SMILES) to unstructured lab documents and instrument data
Engineer sophisticated hybrid search pipelines that blend sparse (keyword), structured (metadata), and dense (vector) retrieval. You will go beyond out-of-the-box OpenSearch to design custom ranking logic, reciprocal rank fusion, and relevance tuning that surfaces the exact “needle in the haystack” for drug discovery
Own and operate the Search Platform infrastructure, ensuring high availability, scalability, performance, and observability across indexing, embedding generation, and query execution
Develop and maintain backend services and APIs in Python and TypeScript that power search capabilities for scientists, data engineers, and AI applications
Collaborate with Applied AI Scientists to integrate embeddings, transformer models, and chemical fingerprints into production search workflows
Architect and implement scientific entity resolution and knowledge graph pipelines to transform raw text into interconnected knowledge. You will design systems that extract and link chemical and biological entities (NER/NED) from unstructured documents, enabling the search engine to “understand” relationships between compounds, targets, and assays
Continuously improve search quality through evaluation metrics such as precision@K, recall@K, MRR, and relevance testing with real scientific use cases
Ensure security, compliance, and tenant isolation as part of operating search services in enterprise bio-pharma environments
Contribute to architectural decisions, technical strategy, and platform-wide improvements to accelerate scientific insight generation
Benefits
Unlimited PTO
100% Company Paid Health, Dental & Vision
Company Paid Life Insurance
401k Savings
Company Paid Disability Insurance
Equity Program- If you are passionate about building scalable search systems, advancing scientific retrieval, and supporting production scale AI workloads, we’d love to talk to you
Experience with large-scale data platforms such as Databricks, Lakehouse architectures, or distributed indexing systems
10+ years of backend or platform engineering experience building distributed, production grade systems
Hands-on experience with search technologies such as Elasticsearch/OpenSearch, Lucene, or vector databases
Familiarity with scientific or unstructured data processing, such as documents, tables, analytical results, or experimental datasets
Experience building and operating microservices or search infrastructure on cloud platforms (AWS preferred), including containerization, CI/CD, observability, and performance tuning
Excellent communication and collaboration skills comfortable working alongside scientists, AI researchers, and product teams