Forward Deployed Engineer

At Arrayo, we don’t just build software - we build intelligent systems that think, adapt, and accelerate real-world science and manufacturing. Our engineers are fluent in AI-augmented development and deploy production systems at a pace that would be impossible without it.We’re hiring Forward Deployed Engineers across multiple levels who combine scientific domain expertise with modern AI-native software engineering. This is a high-autonomy, customer-embedded role for engineers who use AI as a core part of how they design, write, test, and ship code.This track focuses on chemistry, materials science, and industrial manufacturing environments.The RoleAs a Forward Deployed Engineer at Arrayo, you will embed with scientific and industrial teams to understand how their labs and plants truly operate. You will architect and deploy AI-enabled systems that transform fragmented workflows into intelligent, automated processes.AI fluency is not optional in this role. You will:Use AI tools to accelerate development, testing, debugging, and documentationDesign agent-driven workflows that automate complex scientific and operational tasksBuild systems where AI is embedded into the product itself - not layered on as an afterthoughtRapidly prototype, validate, and productionize solutions in days or weeksYou are expected to operate as a force multiplier - leveraging AI to extend your individual engineering output and impact.What You’ll DeliverAI-powered scientific workflows for materials analysis, formulation optimization, and process controlIntelligent integrations between industrial hardware (PLCs, lab instrumentation, control systems) and enterprise platforms (MES, ERP, LIMS, SCADA)Real-time data pipelines that clean, contextualize, and structure experimental and manufacturing dataAgentic systems that assist scientists and engineers in decision-makingProduction-grade full-stack applications that make advanced AI capabilities intuitive and accessibleDeployments that scale from pilot environments to enterprise-wide adoptionCore ExpectationsAI-Native EngineeringComfort using AI coding assistants and tooling as part of your daily development workflowAbility to design systems that incorporate LLMs, automation agents, and machine learning componentsUnderstanding of prompt engineering, evaluation, observability, and model limitationsPragmatic judgment about when to use AI - and when not toTechnical ExecutionStrong full-stack capabilities across backend systems, APIs, data engineering, and frontend developmentExperience building and maintaining reliable data pipelines for complex datasetsAbility to write production-ready, maintainable code under tight iteration cyclesDomain ExpertiseBackground in chemistry, materials science, chemical engineering, or related fieldExperience operating in industrial or manufacturing contextsCommunication & OwnershipComfortable interfacing with executives, scientists, and operatorsClear communicator who can translate between technical and domain stakeholdersWillingness to travel for on-site collaboration and deploymentNice to HaveExperience deploying AI/ML systems in production environmentsBackground in controls engineering or industrial automationExperience with scientific computing ecosystems (Python, data analysis, modeling tools)Experience building modern web applicationsWhat Makes Someone Exceptional HereAI-Leveraged – You treat AI as a core engineering primitive, not a novelty.Outcome-Focused – You prioritize deployed systems and measurable results.Systems-Oriented – You understand the interplay between hardware, software, and data.Comfortable in Ambiguity – You can define structure in chaotic environments.Relentlessly Practical – You optimize for what works in production, not what looks elegant in theory.