Hybrid | AI/ML Engineer $70-$200/hour

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. #J-18808-Ljbffr 24-Mag Llc