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Job Description: Role Description

We’re hiring a Frontend Software Engineer to help build the core user-facing components of our agent platform. In this role, you’ll take ownership of developing intuitive interfaces that make complex AI systems usable for non-technical warfighters. You’ll work closely with machine learning engineers, military users, and product leadership to design and deploy full-stack AI applications that blend advanced agentic retrieval-augmented generation (RAG) with human in the loop, natural language processing (NLP), and system orchestration. This is a high-impact, full-time role from our Austin, TX office.


Duties and Responsibilities 
Design and develop AI applications leveraging Python and TypeScript, with a focus on delivering scalable and maintainable software solutions. 
Collaborate with cross-functional teams to define application requirements, architecture, and technical specifications. 
Implement machine learning models and AI algorithms into production-ready applications, ensuring efficiency and accuracy. 
Build end-to-end AI solutions, including data preprocessing, model integration, and user interface development. 


Required Qualifications

Minimum of 3 years of professional experience in software development, with a strong focus on AI application development. 
Proficient in TypeScript and web application development (Nextjs, React) with demonstrated experience in building, deploying, and maintaining software applications. 
Hands-on experience with large language model (LLM) development, including prompt engineering, tool calling, RAG frameworks and vector databases. 
Strong problem-solving skills, attention to detail, and ability to work both independently and collaboratively. 
Excellent communication skills and the ability to translate technical concepts into practical solutions. 
US Citizenship & Secret and TS / SCI Security Clearance Eligible 


Preferred Qualifications 
Working knowledge of DoD cybersecurity and compliance frameworks, such as NIST 800-171, RMF, or CMMC. 
Skilled in modern development workflows, including Git, CI/CD, and containerization (e.g., Docker), and cloud architectures (AWS) 
Proficiency in Geographic Information Systems (GIS), with the ability to integrate spatial data into machine learning workflows and support geospatial analysis. 
Familiarity with common LLM frameworks and SDKs 
Python proficiency