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Open nowFirst seen 5 days ago

Hybrid | AI/ML Engineer — $70–$200/hour

24-MAG343 open roles

Pay
$70 – $200 an hour
Where
Washington D.C., District of Columbia, United States, Remote
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Your applicationOpen nowHybrid | AI/ML Engineer — $70–$200/hour24-MAG · Washington D.C., District of Columbia, United States, Remote

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 5 days ago

24-MAG median: 1 days open

The posting

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.

Key Responsibilities

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

Ideal Profile

  • 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

Engagement Details

  • Full-time engagement
  • Hybrid
  • Compensation: $70–$200/hour
  • Work will involve production AI/ML engineering, LLM systems, RAG, agentic workflows, cloud deployment, data infrastructure, and secure technical integration
  • Experience in government or highly regulated environments is particularly relevant
  • Strong collaboration with product, security, engineering, and data teams is central to the role
  • Technical scope may include mission-critical systems and environments with elevated security or compliance requirements
  • Role responsibilities and technical priorities may evolve as projects and deployment requirements change

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

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