Company
Technology
StaffSoftwareEngineer,Fullstack(ACF)
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Software Engineer, Fullstack (ACF). Skills: Fullstack engineering, LLM-powered capabilities, RAG pipelines. Design end-to-end fullstack features. Build frontend interfaces”
What You'll Achieve.
Ensure accurate and safe outputs; Ensure trustworthy user experiences
Industry & Context.
Troubleshooting
Section 508–compliant
What They're Looking For.
Must Have
Experience designing and implementing RAG-based LLM systems, Design and optimize multi-step LLM/agent workflows, Hands-on experience with prompt engineering, Fullstack engineering skills, Solid understanding of system design, Experience working in cross-functional, iterative product teams, Familiarity with secure software development practices
Nice to Have
Experience with Python, FastAPI experience, LangChain experience, Postgres with pgvector experience, Next. js experience, Modern cloud/AI infrastructure tools experience, Experience in regulated environments, Experience in public-sector environments, Experience in high-trust environments
What You'll Do.
Design end-to-end fullstack features
Build frontend interfaces
Build backend services
Engineer LLM-powered capabilities
Optimize LLM-powered capabilities
Develop accessible user interfaces
Develop secure user interfaces
Develop Section 508–compliant user interfaces
Develop compliant systems
Evaluate AI-driven interactions
Monitor AI-driven interactions
Improve reliability of AI-driven interactions
Improve safety of AI-driven interactions
Improve quality of AI-driven interactions
Build secure software systems
Build compliant software systems
Maintain secure software systems
Maintain compliant software systems
Collaborate in a cross-functional environment
Contribute to engineering excellence
How You'll Work.
Team & Collaboration
Cross-functional environment; Product managers; Designers; Researchers; Engineers
Full Job Description
## Accountabilities Design and build end-to-end fullstack features, including frontend interfaces, backend services, and APIs supporting a large-scale public digital platform. Engineer and optimize LLM-powered capabilities such as RAG pipelines, semantic search, prompt design, embeddings, and agent-based workflows to ensure accurate and safe outputs. Develop accessible, secure, and Section 508–compliant user interfaces and systems that meet federal standards and serve diverse user needs. Evaluate, monitor, and improve the reliability, safety, and quality of AI-driven interactions to ensure trustworthy user experiences. Build and maintain secure, compliant software systems aligned with federal security requirements and best practices in vulnerability prevention. Collaborate in a cross-functional environment with product managers, designers, researchers, and engineers to deliver iterative, user-centered solutions. Mentor peers and contribute to engineering excellence through best practices in testing, CI/CD, system design, and scalable architecture. Requirements: Strong experience designing and implementing RAG-based LLM systems, including semantic search and knowledge-grounded generation. Proven ability to design and optimize multi-step LLM/agent workflows for data retrieval, refinement, and synthesis. Hands-on experience with prompt engineering, embedding models, and improving LLM response quality and reliability. Strong fullstack engineering skills with the ability to write clean, reusable, and well-tested code across frontend and backend systems. Solid understanding of system design, data modeling, and distributed systems with attention to performance, scalability, and reliability. Experience working in cross-functional, iterative product teams with a strong user-centered engineering mindset. Familiarity with secure software development practices and awareness of compliance and vulnerability mitigation techniques. Bonus: experience with Python, FastAPI, LangChain,
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