> Markdown version of [/jobs/ext/4721179-ai-full-stack-developer](https://www.wearedevelopers.com/jobs/ext/4721179-ai-full-stack-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Full Stack Developer

- **Company:** Mountain LTD
- **Location:** Washington, DC, United States (Remote available)
- **Salary:** $93,600 - $114,400
- **Contract:** Contract
- **Skills:** Adobe Analytics, JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, JIRA, Automation of Tests, Microsoft Azure, Continuous Integration, Python (Programming Language), Machine Learning, NoSQL, Open Web Application Security, Scrum Methodology, Search Technologies, Secure Coding, Software Engineering, Systems Integration, TypeScript, Web Content Accessibility Guidelines, Web Application Frameworks, Google Cloud, Cloud Platform System, GitHub Copilot, ReactJS, Retrieval-Augmented Generation, Large Language Models, Google Vertex AI, Hallucination Detection, Generative AI, Backend, Agentic-AI, Git, AI Platforms, AngularJS, Kubernetes, Information Technology, Amazon Bedrock, Machine Learning Operations, Front End Software Development, Virtual Agents, Api Gateway, Restful APIs, Model Context Protocol, Model Inference, Human in the Loop, Docker, Databricks, Vulnerability Analysis
- **Published:** November 14, 2026
- **Apply:** https://www.dice.com/job-detail/5a059a96-a146-4741-b35a-5b7cd138e6f6

## About the Role

* Bachelor's degree in Computer Science, Engineering, Mathematics, InformationSystems, or a related fi eld and 5+ years of relevant experience, including 5+ years ofhands-on full-stack software development spanning front-end and back-endtechnologies; equivalent experience may substitute for the degree.
 * 1+ year of hands-on experience delivering Generative AI capabilities, such as LLM integration, RAG pipelines, embeddings, vector databases, or AI workflow orchestration.
 * Strong proficiency in Python, JavaScript/TypeScript, and a modern front-end framework (e.g., React or Angular), with experience designing RESTful APIs, working with relational and NoSQL databases, and developing on a major cloud platform(AWS, Azure, or Google Cloud) with containers (Docker/Kubernetes) and CI/CD pipelines.
 * Experience with automated testing and evaluating AI output quality (accuracy, relevance, hallucination), secure coding practices and federal security requirements, and building interfaces that conform to Section 508 / WCAG 2.1 A and AA within Agile teams using Git and Jira.
 * Generative AI or Machine Learning certifi cation (e.g., Microsoft Azure AI, AWSGenerative AI/ML, Google Cloud, Databricks, Snowfl ake SnowPro, NVIDIA, or Certifi edArtifi cial Intelligence Practitioner (CAIP)).
 * 7+ years of software development experience, including support of federal agency programs.
 * Experience with agentic AI frameworks, Model Context Protocol (MCP) tooling, open-weight model serving, and vector stores, including testing AI systems for securityvulnerabilities (e.g., prompt injection) and Authority to Operate (ATO) documentation.
 * Knowledge of AWS Cloud AI development services, Amazon Bedrock, AmazonSageMaker, Lambda, and API Gateway, for building and deploying generative AI andagentic workloads; the Government's AI engineering environment currently spansAzure AI Foundry, Google Vertex AI, and AWS Bedrock.

## Description

* Design, develop, and enhance AI-enabled full-stack applications as part of a small,forward-deployed team, from accessible front-end interfaces (Section 508 / WCAG2.1 A and AA) to back-end APIs, services, and workflow automation.
 * Build Large Language Model (LLM) integrations, Retrieval-Augmented Generation(RAG) pipelines, vector search, and agentic AI workfl ows using Model ContextProtocol (MCP)-based tools, engineered to the government's AI agent securityframework (OWASP Top 10 for LLM Applications, NIST AI RMF) with promptengineering, retrieval quality controls, and human-in-the-loop oversight.
 * Plan and execute functional, performance, and AI-specifi c adversarial testing (promptinjection and jailbreaks), evaluating outputs for accuracy, hallucination, bias, andsafety; build and maintain CI/CD and MLOps pipelines with security scans and Test,Evaluation, Verifi cation and Validation (TEVV) gates, and prepare release artifacts.
 * Monitor production AI systems, perform root-cause analysis, support incident response and scheduled helpdesk support, and contribute to Responsible AI documentation (model cards, impact assessments); participate in two-week Agile sprints using Government-furnished AI engineering tools (e.g., GitHub Copilot, with model inference via Azure AI Foundry, Google Vertex AI, or AWS Bedrock), taking part in code and prompt reviews under the same review and security gates as hand-written code, and keeping code, prompts, and documentation in Government-approved repositories with full traceability.