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# Full Stack AI Engineer

- **Company:** Information Gateways Inc
- **Location:** Alexandria, VA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, Document Management Systems, Github, Spring Framework, Python (Programming Language), Machine Learning, Node.Js, Rapid Prototyping Process, Search Technologies, Data Ingestion, DevOps Tools - Open-source, ReactJS, Large Language Models, Generative AI, Backend, Gitlab, Cloudformation, Fastapi, Vue.js, AngularJS, Kubernetes, Machine Learning Operations, Api Design, Api Gateway, Terraform, Automation Anywhere, Docker, Microservices, Data Generation
- **Published:** September 3, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9140005/full-stack-ai-engineer

## About the Role

* Experience building full stack applications using frameworks such as React, Angular, or Vue; and backend frameworks such as Node.js, Python FastAPI, or Java Spring.
 * Hands-on experience applying machine learning or LLM capabilities in production or near production environments.
 * Strong Python skills for AI workflows and API development.
 * Experience with AWS services (e.g., Lambda, S3, ECS/EKS, API Gateway, CloudFormation/Terraform).
 * Familiarity with vector search, embeddings, RAG architectures, or NLP/LLM-driven systems.
 * Experience with DevOps tooling (GitLab/GitHub CI/CD, Docker, Kubernetes).
 * Ability to work directly with clients, refine requirements, and deliver iterative prototypes quickly.

## Description

* Design, develop, and deploy AI enabled full stack applications that support document processing, intelligent search, generative AI use cases, and agentic workflows.
 * Implement and integrate reusable AI accelerators such as RAG pipelines, model orchestration layers, hybrid search components, and structured data generation capabilities.
 * Develop secure, cloud native backend APIs and microservices (preferably AWS based), data ingestion, and workflow automation.
 * Collaborate with data scientists to train, fine tune, or evaluate machine learning and LLM models implemented within client systems.
 * Apply LLMOps best practices for model lifecycle, experimentation, telemetry, CI/CD, testing, and monitoring.
 * Ensure solutions comply with client security requirements, federal accessibility standards, and responsible AI principles.
 * Support rapid prototyping as well as hardening prototypes to production-grade systems aligned to client modernization initiatives (e.g., intelligent document management, NLP-driven search, cloud migration).
 * Participate in sprint ceremonies, backlog refinement, and joint design sessions with product owners and technical leads.
 * Produce documentation, architecture diagrams, and deployment artifacts.


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