Staff Software Engineer, Full StackArcher is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.What You'll Do:We are looking for a versatile Staff Software Engineer, Full Stack with a specialization in Data Engineering to own the design, development, and maintenance of Archer's internal tooling ecosystem.
In this role, you will act as a force multiplier for the entire organization—from Hardware Engineers analyzing flight data, to Talent Acquisition teams scaling our workforce.You will not just be writing code; you will be architecting the data infrastructure and pipelines that power Archer's internal platforms. From raw flight test data to production-ready datasets, APIs, and applications.Responsibilities:Develop scalable full-stack web applications that automate workflows for engineering, operations, and other stakeholders across the businessWork directly with internal customers to gather requirements, iterate on UI/UX, and drive adoption of new tools and other stakeholders.Develop, deploy and scale time series datasets and enable analytics, anomaly detection & visualization over them.Own data orchestration using tools like Prefect or Apache Airflow to schedule, monitor, and scale recurring data workflows.Work with our Data Engineering Team to build a custom web app to conduct complex data reviews following flight tests. Partner with key engineering stakeholders to iterate on new features and drive adoption.Manage the CI/CD pipelines and cloud infrastructure required to host internal tools securely.Mentor a team of engineers working on deploying custom internal tools.What You Need:4+ years of professional experience in full-stack software developmentBachelor's or Master's Degree in Computer Science, Aerospace Engineering, Data Analytics, or a related fieldDeep expertise with backend building RESTful APIs and scalable containerized applications through Kubernetes or related frameworksExpertise with one or more cloud data platforms (AWS, Azure, or GCP)Experience with designing data models for custom complex applicationsHands-on experience integrating Gen AI via API and a familiarity with employing RAG in custom applicationsKnowledge of visualization technologies such as D3.js, Plotly, Grafana, Superset, or related technologies.Exceptional analytical skills, attention to detail, and the ability to collaborate effectively across multidisciplinary teamsClear communication skills that are essential for working across diverse stakeholdersBonus Qualifications:Solid foundation in building tools for hardware, IoT, especially processing and analyzing time-series dataExperience building with Model Context Protocol (MCP) servers to connect data sources to LLMsPrevious experience with coaching and managing a small engineering teamExperience with Infrastructure as Code (Terraform, CloudFormation)Experience in aerospace or a related field, particularly with flight test data analysis and aircraft health monitoringPlease note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications.At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business.
We drive a pay-for-performance culture and reward performance that supports the Company's business strategy. For this position we are targeting a base pay between $173,000 - $216,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.