Leads development of scalable backend systems, distributed architectures, and agentic capabilities for federal customers, managing full feature lifecycles from requirements to deployment on classified networks. Requires full-stack proficiency, cloud-native tech, data engineering, and AI integration expertise.
162k – 311k/yr
On-siteBackend Engineering
About the role
Responsibilities
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 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.
Requirements
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).
Data Engineering: Knowledge of ETL 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.
Build and maintain backend systems, APIs, data models, and services for scalable code security products. Requires strong knowledge of databases, distributed systems, and query optimization; experience with Python/Flask preferred.
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