AI/ML Software Developer
Résumé du poste par JobGrid
AI/ML Software Developer at InterImage: Arlington, États-Unis; Hybride; Temps plein; Senior; IT. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Arlington, États-Unis, Hybride
- Role classification: IT, Ingénieur Full Stack, Temps plein, Senior
- Source freshness: checked by JobGrid on 2026-05-28.
- Application path: candidates continue to the employer application page with non-personal referral tags.
**Secret OR Top Secret Clearance Required**
We are seeking a highly skilled Full Stack Developer with strong software design expertise to design, build, and scale modern applications that integrate data-intensive systems and Generative AI capabilities. This role sits at the intersection of software engineering, data engineering, and AI innovation, supporting the development of enterprise solutions that leverage large datasets and advanced language models.
You will work closely with cross-functional teams to architect, develop, and deploy scalable applications, while helping drive the integration of LLM/GenAI technologies into production environments.
Key Responsibilities
Full Stack Development
- Design, develop, and maintain end-to-end web applications (front-end, back-end, and APIs)
- Build scalable backend services using Python frameworks (e.g., Flask, FastAPI, Django)
- Develop responsive, user-friendly front-end interfaces using modern frameworks (React, Angular, or similar)
- Architect and implement RESTful and/or GraphQL APIs
- Ensure application performance, scalability, and security across the stack
Database & Data Engineering
- Design, develop, and optimize relational and/or NoSQL database systems
- Create efficient data models and schemas to support large-scale applications
- Develop scripts and pipelines to ingest, transform, and manage data flows
- Troubleshoot performance bottlenecks and ensure data integrity
- Work with large, complex datasets to enable analytics and AI use cases
Generative AI / LLM Integration
- Build, test, and deploy LLM-powered applications and workflows
- Integrate Generative AI capabilities into existing platforms and user experiences
- Evaluate and assess LLM outputs for performance, accuracy, and usability
- Implement Retrieval-Augmented Generation (RAG) pipelines and vector database integrations
- Support fine-tuning, prompt engineering, and optimization of models for mission-specific use cases
System Design & Architecture
- Contribute to the design of scalable, distributed system architectures
- Collaborate with engineers to integrate AI components into enterprise environments
- Balance tradeoffs between performance, cost, and scalability
- Support CI/CD pipelines and DevSecOps best practices for deployment
Client & Mission Support
- Translate ambiguous requirements into technical solutions
- Help stakeholders understand evolving AI/technology options
- Provide guidance on best practices for integrating AI into business workflows