Senior Software Engineer, Public Sector

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: • Create multi-layered guardrails around agents • Optimize data retrieval for agents • Orchestrate fleets of asynchronous agents • Automatically alerts users to deviations in data • Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. • Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. • Direct the orchestration of asynchronous agent fleets to meet mission requirements. • Lead customer engagements to translate mission needs into technical requirements. • Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. • Conduct technical reviews and identify risks within machine learning infrastructure and model serving. • Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: • Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases • Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus • Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles • AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial. • Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles • Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment • Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. g