We are sharing a specialised full-time opportunity for experienced Forward Deployed Engineers to work at the intersection of applied AI, machine-learning infrastructure, data intelligence, and partner-facing technical implementation.
Selected professionals will work directly with leading AI research and enterprise teams to translate complex or ambiguous AI problems into scoped technical projects and production systems. The role combines research collaboration, ML and evaluation infrastructure, large-scale data systems, LLM applications, and hands-on engineering across the full lifecycle from discovery and architecture through deployment, iteration, and partner success.
Key Responsibilities
Applied AI & Partner-Facing Engineering
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Work directly with AI research teams and enterprise partners to define research goals, technical requirements, and project direction
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Translate ambiguous AI and machine-learning problems into clearly scoped technical projects
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Act as a technical implementation partner across research, engineering, product, and stakeholder teams
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Move comfortably between research questions, technical architecture, hands-on engineering, and partner-facing execution
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Own technical systems from initial discovery through implementation, deployment, iteration, and ongoing reliability
ML Infrastructure & Data Intelligence
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Build large-scale data-intelligence systems for collecting, organising, evaluating, and improving training and evaluation data
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Implement ML pipelines supporting data curation, model training, evaluation, experimentation, and continuous improvement
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Develop infrastructure for model inference, experimentation, evaluation, and deployment
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Design reliable technical workflows that support advanced AI research and production environments
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Build and maintain systems capable of supporting complex data and machine-learning workloads
LLM Applications & Agentic Systems
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Develop LLM applications including multi-agent systems, tool-using agents, RAG workflows, and human-in-the-loop systems
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Build evaluation harnesses and infrastructure for assessing agent and model behaviour
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Develop systems that extend one-off AI experiments into reliable, repeatable, multi-turn workflows
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Implement agentic automation across technically complex business and research processes
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Apply modern LLM tooling and model-evaluation approaches to production-oriented AI systems
Data Quality, Taxonomy & Evaluation
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Design data taxonomies, labelling systems, evaluation rubrics, and quality frameworks
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Improve dataset structure and quality to support stronger model performance and research outcomes
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Develop workflows for dataset curation, annotation, validation, and quality assurance
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Analyse data and model behaviour to identify opportunities for system improvement
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Apply rigorous standards to training data, evaluation datasets, and research workflows
Ideal Profile
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Strong professional experience as a software, machine-learning, applied AI, or infrastructure engineer
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Advanced Python engineering skills with experience building and shipping production systems end to end
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Practical experience with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI automation
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Experience building or maintaining data pipelines, ML infrastructure, model-evaluation systems, or research workflows
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Strong understanding of data quality, taxonomy design, labelling workflows, and dataset curation for AI systems
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Ability to operate independently in ambiguous, partner-facing environments with strong technical and product ownership
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Comfortable working directly with researchers, technical partners, founders, and enterprise stakeholders
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Experience within a startup, AI infrastructure company, applied AI organisation, or research-focused engineering team is advantageous
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Experience building multi-turn agents, agent-evaluation systems, workflow automation, or human-in-the-loop AI is advantageous
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Familiarity with modern LLM tooling, agent frameworks, model-evaluation stacks, and ML experimentation platforms is beneficial
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Experience acting as a technical partner to external customers, research teams, or strategic enterprise accounts is strongly valued
Engagement Details
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Full-time engagement
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Remote role with travel required as needed
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Compensation: $300,000–$650,000/year
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Work will span applied AI, ML infrastructure, data intelligence, LLM systems, agentic workflows, and partner-facing technical delivery
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Responsibilities may cover the full technical lifecycle, including discovery, architecture, implementation, deployment, reliability, and iteration
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Travel may be required for partner-facing collaboration and project execution
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Project scope and research priorities may evolve depending on technical and partner requirements
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
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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