Research Informatics Engineer — AI Data Pipelines (Remote)

Excelsior Sciences of New York; New York (NY); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Job summary

Excelsior Sciences of New York is seeking a Research Informatics / R&D IT professional to build the digital foundation for AI-native drug discovery. You will design cloud-native data platforms, integrate LIMS/ELN and analytical systems, and develop scalable data pipelines to make scientific data machine-actionable.

The role emphasizes agentic AI, multi-agent workflows, and production-grade software practices, collaborating with scientists and engineers in NYC with periodic remote flexibility.

Qualifications

• Master’s degree in Computer Science with cloud/AI coursework.
• Experience building data pipelines and scientific workflows (Spark/Databricks).
• Hands-on with AWS, Docker/Kubernetes, SQL and orchestration tools.
• Strong experience with AI copilots/agents and LLM concepts.
• Familiarity with LIMS/ELN or analytical platforms (Genedata, CDD Vault).
• Proficiency in Python and SQL; additional HPC libraries are a plus.

Responsibilities

• Integrate and extend LIMS/ELN and analytical informatics platforms.
• Design scalable data pipelines and APIs for FAIR, machine-actionable data.
• Build cloud-native components on AWS using containers and CI/CD.
• Prototype agentic AI/GenAI solutions and multi-agent workflows.
• Collaborate with scientists and engineers to translate needs into software.
• Apply agile/AI‑agile methods and improve data quality and observability.

Skills

Data pipelines

Cloud computing

Python

SQL

Docker

Kubernetes

LLM concepts

Multi-agent systems

AI coding assistants

Education

Master’s degree in Computer Science

Tools

Genedata

CDD Vault

Virscidian Analytical Studio

Neo4j

Airflow

Prefect

PostgreSQL

Job description

Excelsior Sciences of New York is seeking a Research Informatics / R&D IT professional to build the digital foundation for AI-native drug discovery. You will design cloud-native data platforms, integrate LIMS/ELN and analytical systems, and develop scalable data pipelines to make scientific data machine-actionable.

The role emphasizes agentic AI, multi-agent workflows, and production-grade software practices, collaborating with scientists and engineers in NYC with periodic remote flexibility.