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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Hybrid - **Company:** 24-MAG LLC - **Location:** Washington, DC, United States - **Salary:** $145,600.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing Security, Continuous Integration, Data as a Services, Data Infrastructure, Extract Transform Load (ETL), DevOps, Python (Programming Language), Machine Learning, Metadata, OpenAI, Gemini Enterprise (Agent Platform), Secure Coding, Software Engineering, Systems Integration, AI Infrastructure, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Software Security, Software Application Programming, Agentic-AI, AI Platforms, Kubernetes, Machine Learning Operations, Api Design, Restful APIs, Data Pipelines - **Published:** October 26, 2026 - **Apply:** https://www.careerjet.com/jobad/us343cfbe91c31e9c7cd4f9d8ad7c2b244 ## About the Role We are sharing a full-time opportunity for an experienced AI/ML Engineer with strong expertise in Python, large language models, retrieval-augmented generation, agentic systems, cloud AI infrastructure, and production-grade machine learning to contribute to secure, mission-critical AI initiatives. The role will focus on designing and deploying advanced AI systems using LLMs, RAG, multi-agent orchestration, secure cloud platforms, and robust data infrastructure. The ideal candidate combines deep hands-on engineering ability with strong systems thinking, production experience, and comfort working in highly regulated or security-sensitive environments., * Strong proficiency in Python for production AI/ML development * Hands-on experience building production systems using LLMs, RAG, and prompt engineering * Experience with multi-agent orchestration, tool use, or agentic AI systems * Familiarity with LangGraph, LangChain, or comparable orchestration frameworks * Strong understanding of cloud AI services and secure deployment environments * Experience with AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock, or related platforms is highly relevant * Background building data pipelines, ETL systems, metadata catalogues, or ontologies * Strong experience with REST APIs and SDK integrations * Understanding of secure coding and modern DevOps practices, including CI/CD * Strong written and verbal communication skills * Experience with government, defence, highly regulated, or compliance-sensitive environments is advantageous * Familiarity with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise is beneficial * Knowledge of advanced API development and metadata or context-management platforms is a plus ## Description LLM & RAG Systems * Design, implement, and optimise production-grade AI/ML systems * Build applications using large language models, retrieval-augmented generation, and prompt engineering * Evaluate and improve model behaviour across complex production use cases * Design reliable retrieval and grounding workflows * Apply strong engineering standards to performance, scalability, and maintainability Agentic AI & Multi-Agent Orchestration * Develop and orchestrate multi-agent systems using modern agent frameworks * Work with platforms such as LangGraph, LangChain, or comparable tooling * Design tool-use workflows and agent interaction patterns * Build reliable control logic for complex multi-step AI tasks * Evaluate agent behaviour, failure modes, and system-level trade-offs Secure Cloud AI Infrastructure * Deploy and integrate AI solutions within secure cloud environments * Work with platforms such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock * Design infrastructure appropriate for sensitive or highly regulated applications * Apply secure engineering practices across development and deployment * Collaborate with security teams to ensure technical solutions align with environment-specific requirements Data Pipelines & Knowledge Infrastructure * Build and maintain robust data pipelines for AI training and inference * Design and manage ETL workflows * Develop metadata catalogues, ontologies, and structured knowledge representations * Improve data quality, lineage, and accessibility across AI systems * Support reliable ingestion, transformation, and retrieval workflows APIs, Integrations & Production Engineering * Build and maintain REST APIs and SDK integrations * Connect AI models, external systems, and data services through reliable interfaces * Apply modern software engineering and secure coding standards * Implement and maintain CI/CD workflows * Support deployment, monitoring, and operational reliability of production AI systems Cross-Functional Technical Leadership * Collaborate closely with product, security, engineering, and data teams * Document technical decisions and architecture clearly * Communicate complex technical concepts to both technical and non-technical stakeholders * Contribute to engineering standards and architecture decisions * Help translate mission requirements into secure and scalable technical solutions