hour

24-Mag•Washington D.C., WA

4d•Hybrid

About The Position

24-MAG LLC is sharing a full-time opportunity for an experienced AI/ML Engineer to contribute to secure, mission-critical AI initiatives. The role focuses on designing and deploying production-grade AI systems using large language models, retrieval-augmented generation (RAG), multi-agent orchestration, secure cloud platforms, and robust data infrastructure. The ideal candidate combines hands-on engineering ability with systems thinking, production experience, and comfort working in highly regulated or security-sensitive environments. The engineer will build and improve LLM and RAG applications, orchestrate agentic systems, deploy AI solutions in secure cloud environments, and create data pipelines and knowledge infrastructure. The role also involves building REST APIs and SDK integrations, supporting CI/CD and production operations, and collaborating with product, security, engineering, and data teams. Technical scope may include mission-critical systems and elevated security or compliance requirements, and priorities may evolve with project and deployment requirements. This hybrid opportunity is available through 24-MAG LLC, which connects experienced professionals with consulting opportunities across technical, evaluation, and project-based workstreams. Compensation is $70–$200 per hour.

Requirements

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.
Strong understanding of cloud AI services and secure deployment environments.
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.

Nice To Haves

Familiarity with LangGraph, LangChain, or comparable orchestration frameworks.
Experience with AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock, or related platforms.
Experience in government, defence, highly regulated, or compliance-sensitive environments.
Familiarity with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
Knowledge of advanced API development and metadata or context-management platforms.

Responsibilities

Design, implement, and optimize production-grade AI/ML systems.
Build applications using large language models, retrieval-augmented generation, and prompt engineering; evaluate and improve model behavior across production use cases.
Design reliable retrieval and grounding workflows and apply engineering standards for performance, scalability, and maintainability.
Develop and orchestrate multi-agent systems using modern agent frameworks; design tool-use workflows, agent interaction patterns, and control logic for complex multi-step tasks.
Evaluate agent behavior, failure modes, and system-level trade-offs.
Deploy and integrate AI solutions within secure cloud environments and apply secure engineering practices across development and deployment.
Collaborate with security teams to align technical solutions with environment-specific requirements.
Build and maintain data pipelines and ETL workflows for AI training and inference.
Develop metadata catalogues, ontologies, and structured knowledge representations; improve data quality, lineage, and accessibility.
Support reliable data ingestion, transformation, and retrieval workflows.
Build and maintain REST APIs and SDK integrations that connect AI models, external systems, and data services.
Apply modern software engineering and secure coding standards; implement and maintain CI/CD workflows.
Support deployment, monitoring, and operational reliability of production AI systems.
Collaborate with product, security, engineering, and data teams.
Document technical decisions and architecture, communicate technical concepts to varied audiences, contribute to engineering standards and architecture decisions, and translate mission requirements into secure, scalable solutions.