Hybrid
$70 per hourJobleads-US
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 Jobleads-USVacancy posted 3 days ago
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