Remote GenAI Engineer (Forward-Deployed) | Equity

Gravitas Group; United States; A distancia; USD 85.000 - 104.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity package

Annual bonus

Descripción de la vacante

Gravitas Group is seeking a Forward-Deployed Engineer (GenAI) to design, prototype, and productionise GenAI solutions for financial services clients. This remote role involves occasional travel to London and client sites as needed.

You will collaborate with senior stakeholders to translate business requirements into scalable AI systems, deploy LLM-based agents, and drive ROI from PoC to production, blending deep technical execution with customer impact.

Formación

• 2+ years building production AI/data solutions (FDE/Data Scientist/AI Engineer)
• Hands-on GenAI with LLMs, prompts, retrieval pipelines
• Strong Python proficiency
• ML model development, deployment & monitoring
• Ability to translate business problems into computational workflows
• Excellent communication with senior stakeholders

Responsabilidades

• Collaborate with client teams to understand domain challenges and success metrics
• Translate business requirements into scalable AI solutions using the agentic framework
• Prototype and deploy LLM-based agents (prompt structures, orchestration, memory, retrieval pipelines)
• Drive transition from PoC to production with reliability and ROI
• Act as trusted technical advisor guiding adoption and metrics
• Contribute reusable components and frameworks for faster deployments

Conocimientos

GenAI experience

Python

ML engineering

Stakeholder communication

LLMs

Prompt engineering

LangChain

LlamaIndex

Herramientas

Vector databases

DSPy

LangChain

Descripción del empleo

Gravitas Group is seeking a Forward-Deployed Engineer (GenAI) to design, prototype, and productionise GenAI solutions for financial services clients. This remote role involves occasional travel to London and client sites as needed.

You will collaborate with senior stakeholders to translate business requirements into scalable AI systems, deploy LLM-based agents, and drive ROI from PoC to production, blending deep technical execution with customer impact.