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
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Design, implement, and optimise production-grade AI/ML systems
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Build applications using large language models, retrieval-augmented generation, and prompt engineering
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Evaluate and improve model behaviour across complex production use cases
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Design reliable retrieval and grounding workflows
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Apply strong engineering standards to performance, scalability, and maintainability
Agentic AI & Multi-Agent Orchestration
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Develop and orchestrate multi-agent systems using modern agent frameworks
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Work with platforms such as LangGraph, LangChain, or comparable tooling
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Design tool-use workflows and agent interaction patterns
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Build reliable control logic for complex multi-step AI tasks
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Evaluate agent behaviour, failure modes, and system-level trade-offs
Secure Cloud AI Infrastructure
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Deploy and integrate AI solutions within secure cloud environments
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Work with platforms such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock
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Design infrastructure appropriate for sensitive or highly regulated applications
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Apply secure engineering practices across development and deployment
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Collaborate with security teams to ensure technical solutions align with environment-specific requirements
Data Pipelines & Knowledge Infrastructure
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Build and maintain robust data pipelines for AI training and inference
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Design and manage ETL workflows
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Develop metadata catalogues, ontologies, and structured knowledge representations
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Improve data quality, lineage, and accessibility across AI systems
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Support reliable ingestion, transformation, and retrieval workflows
APIs, Integrations & Production Engineering
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Build and maintain REST APIs and SDK integrations
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Connect AI models, external systems, and data services through reliable interfaces
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Apply modern software engineering and secure coding standards
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Implement and maintain CI/CD workflows
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Support deployment, monitoring, and operational reliability of production AI systems
Cross-Functional Technical Leadership
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Collaborate closely with product, security, engineering, and data teams
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Document technical decisions and architecture clearly
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Communicate complex technical concepts to both technical and non-technical stakeholders
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Contribute to engineering standards and architecture decisions
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Help translate mission requirements into secure and scalable technical solutions
Ideal Profile
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Strong proficiency in Python for production AI/ML development
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Hands-on experience building production systems using LLMs, RAG, and prompt engineering
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Experience with multi-agent orchestration, tool use, or agentic AI systems
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Familiarity with LangGraph, LangChain, or comparable orchestration frameworks
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Strong understanding of cloud AI services and secure deployment environments
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Experience with AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock, or related platforms is highly relevant
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Background building data pipelines, ETL systems, metadata catalogues, or ontologies
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Strong experience with REST APIs and SDK integrations
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Understanding of secure coding and modern DevOps practices, including CI/CD
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Strong written and verbal communication skills
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Experience with government, defence, highly regulated, or compliance-sensitive environments is advantageous
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Familiarity with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise is beneficial
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Knowledge of advanced API development and metadata or context-management platforms is a plus
Engagement Details
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Full-time engagement
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Hybrid
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Compensation: $70–$200/hour
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Work will involve production AI/ML engineering, LLM systems, RAG, agentic workflows, cloud deployment, data infrastructure, and secure technical integration
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Experience in government or highly regulated environments is particularly relevant
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Strong collaboration with product, security, engineering, and data teams is central to the role
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Technical scope may include mission-critical systems and environments with elevated security or compliance requirements
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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.
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