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
• Strong understanding of semantic search concepts embeddings, transformers, similarity scoring, ranking logic, relevance tuning, hybrid retrieval
• Exposure to NLP, LLMs, embedding generation, or retrieval-augmented workflows
• Strong problem solving skills, with the ability to navigate ambiguous scientific workflows and translate them into engineered systems
• Expert-level coding skills in TypeScript and Python building robust APIs and backend services
• Experience with cheminformatics tools and libraries (e.g., RDKit), including molecular fingerprints, similarity metrics, or substructure search
• Prior experience implementing chemical search systems, such as SMILES parsing, normalization, or chemical indexing
• Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG