Forward Deployed Engineer

Elite Virtual Brokerage

. Work directly with leading AI labs and enterprise partners to define research goals, technical requirements, and project direction .

Posted 9/15/2026full-timeRemote • United StatesMid-LevelSenior💰 $180,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying large-scale AI systems, with a strong focus on ML pipelines, data quality, and LLM applications. Proven ability to translate complex AI challenges into actionable projects while collaborating with technical partners and stakeholders.

Highest-signal resume keywords

Python Engineering SkillsLLM Application DevelopmentData Pipeline ManagementML Infrastructure DevelopmentData Taxonomy Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData CurationModel TrainingModel EvaluationData QualityTaxonomy DesignLabeling WorkflowsAI AutomationMulti-Turn WorkflowsHuman-in-the-Loop Systems

Soft Skills

Technical OwnershipIndependent OperationPartner-Facing Communication

Tools & Technologies

ML Experimentation PlatformsEvaluation HarnessesAgent FrameworksData Annotation SystemsRAG Workflows

Industry Keywords

AI LabsEnterprise PartnersApplied AIAI InfrastructureResearch Workflows

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Work directly with leading AI labs and enterprise partners to define research goals, technical requirements, and project direction
Build large-scale data intelligence systems for collecting, organizing, evaluating, and improving training and evaluation data
Implement ML pipelines for data curation, model training, evaluation, experimentation, and continuous improvement
Design data taxonomies, labeling systems, and quality frameworks to improve dataset structure, model performance, and research outcomes
Develop LLM applications, including multi-agent systems, tool-using agents, RAG workflows, evaluation harnesses, and human-in-the-loop systems
Translate ambiguous AI problems into scoped technical projects and production systems with research and engineering teams
Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms
Build systems that help partners move from one-off AI experiments to reliable, repeatable, multi-turn agent workflows
Own systems across discovery, architecture, implementation, deployment, reliability, iteration, and partner success

Requirements

What you’ll need

Able to operate independently in ambiguous, partner-facing settings with strong technical and product ownership
Strong Python engineering skills with experience building and shipping production systems end to end
Experience working with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI automation
Experience building or maintaining data pipelines, ML infrastructure, evaluation systems, or research workflows
Strong understanding of data quality, taxonomy design, labeling workflows, and dataset curation for AI systems
Comfortable working directly with technical partners, researchers, founders, and enterprise stakeholders
Preferred: background at a startup, AI infrastructure company, applied AI company, or research-focused engineering team
Preferred: experience building systems for multi-turn agents, agent evaluation, workflow automation, or human-in-the-loop AI
Preferred: experience designing data taxonomies, annotation systems, evaluation rubrics, or dataset quality pipelines
Preferred: experience acting as a technical partner to external customers, research teams, or strategic enterprise accounts
Preferred: familiarity with modern LLM tooling, agent frameworks, model evaluation stacks, and ML experimentation platforms

Benefits

Comp & perks

Equity compensation
Performance-based bonuses
Up to 100% reimbursement for health-insurance premiums
Paid time off
401(K) plan with a company match
Additional benefits designed to support a high-performing, remote-first workforce