Drug Discovery Automation Software Engineer

Deerfield Management Companies•New York, NY

1d•Onsite

About The Position

Excelsior Sciences is revolutionizing small-molecule discovery and manufacturing using Blocc chemistry, a modular and automation-friendly approach designed for machine execution and AI learning. This is complemented by closed-loop AI learning systems. The company is supported by significant funding, including a $70M Series A from prominent investors and a $25M grant from the Empire State Development. Excelsior Sciences is building a lean, high-leverage organization at the intersection of chemistry, automation, software, and AI. Located at the Cure building in New York City, the company aims to establish a chemistry and AI-native discovery platform where high-quality experimental data continuously informs learning systems to guide molecular design, experimentation, and discovery. This role is part of the Automation team (Physical AI & Lab IT), reporting to the Chief Physical AI Officer. The team collaborates with Research Informatics / Software Engineering and Frontier AI (foundation models & AI/Quantum). The Automation team is responsible for the software and systems that link physical lab devices and robotic platforms with digital lab data and AI agents, enabling reliable, agentic control of automated workflows and closed-loop experimentation. Additionally, this role serves as the Primary Service Owner for all Lab IT Support at Excelsior Sciences, overseeing lab computer lifecycle, warranty support, setup, configuration, endpoint security, remote access, and lab backup infrastructure. The ideal candidate will possess strong software engineering skills, practical knowledge of lab instrumentation, and hands-on experience in Lab IT ownership. Success will be measured by the dependability, observability, and machine-actionability of automated lab workflows, alongside a secure, supported, and operational lab computing environment.

Requirements

BS or MS in Computer Science, Software Engineering, Bioengineering, Life Sciences, or a related field.
3 to 5 years of experience in digital or laboratory automation, ideally within pharmaceutical, biotech, or high-throughput research environments.
Proficiency in Python and at least one JavaScript/TypeScript, C#, or R; experience with software development best practices (version control, testing, code review, CI).
Hands-on experience with software automation and integration approaches (REST APIs, device SDKs, messaging, or equivalent).
Familiarity with LIMS, ELNs, digital orchestration/scheduling software, and/or cloud platforms (including Azure) used in research settings.
Practical understanding of laboratory instrumentation and automation technologies; ability to troubleshoot across software and physical systems.
Hands-on experience with Windows endpoint configuration, Azure AD/Entra join or similar identity integration, endpoint security tools (e.g., SentinelOne or equivalent), remote access solutions, and backup platforms (e.g., Datto or similar).
Strong communication and collaboration skills; the ability to work effectively with scientists and engineers in a fast-paced environment.
Ability to manage multiple projects, work independently, and contribute as part of a cross-functional team; comfort serving as primary owner for operational Lab IT support.

Nice To Haves

Experience building or operating agentic AI / multi-agent systems, RAG pipelines, or orchestration layers that interface with physical or lab systems.
Direct experience with common lab automation platforms (liquid handlers, robotic workcells, integrated schedulers such as Green Button Go, Cellario, Overlord, or similar) and writing control or integration software for them.
Experience with workflow orchestration tools (e.g., Prefect, Airflow, Temporal, Dagster) or building custom orchestration for lab workflows.
Familiarity with data pipelines, instrument data models, and making laboratory data machine-actionable for both humans and AI agents.
Prior work experience in small-molecule, biotherapeutics, or high-throughput discovery environments.
Comfort operating at the boundary of Physical AI, Lab IT, and digital/AI systems in a startup or platform-building context.

Responsibilities

Design, build, and maintain software automation suites and agents that control web and desktop applications driving lab automation devices and integrated workcells.
Develop software tools that automate manual processes and improve reliability, throughput, and data quality of existing automated workflows.
Work closely with scientists and automation engineers to design and implement digital solutions and data workflows, with particular focus on instrument integrations and the hand-off between physical execution and lab data systems.
Build and operate the orchestration and interface layer that allows AI agents (and human operators) to plan, dispatch, monitor, and learn from automated experiments—bridging physical devices and digital/lab-data platforms.
Conduct testing, troubleshooting, and continuous improvement of automated workflows, including root-cause analysis across software, device, and data layers.
Contribute to data management strategies and integrations that make instrument and automation data FAIR, high-quality, and usable by both scientists and AI systems.
Integrate diverse data sources and informatics tools to support holistic analysis and decision-making in early drug discovery.
Stay current on emerging automation, informatics, orchestration, and agentic AI tools relevant to early drug discovery; evaluate and prototype promising approaches.
Provide training and support to research staff on automation and informatics tools and best practices.
Participate in cross-functional meetings to align automation efforts with project and platform goals; uphold high standards of scientific rigor, reliability, and professionalism.
Own warranty support for all computers within the lab environment, coordinating repairs, replacements, and vendor interactions as needed.
Complete Windows configuration into the Azure environment; install and configure N@W remote access software, SentinelOne endpoint protection, and Datto backup client; install any required equipment vendor software so instruments and workstations are ready for scientific use.
Own and maintain the Datto server that backs up lab computers; ensure backup integrity, recovery readiness, and ongoing operational health of the lab backup infrastructure.
Serve as the single point of accountability for Lab IT support needs across Excelsior Sciences, coordinating with the managed services IT team where enterprise network, identity, or broader infrastructure support is required.