Senior AI Engineer - Remote (GCP/AWS/Azure, RAG & LLM)

D2B; United States; Remote; USD 21,000 - 32,000; Full time

Benefits offered by this job

Remote in PH

Australian holidays

Training & growth

No agency middleman

Job summary

D2B seeks a Senior AI Engineer to design and deploy production‑grade AI/ML systems, focusing on LLM-based workflows, RAG, and cloud platforms (GCP, AWS, Azure). You will build retrieval systems, integrate APIs, and drive AI solutions across the SDLC in a fully remote setting.

Responsibilities include translating concepts into production code, supporting from POC to handover, and ensuring scalable, secure architectures across cloud environments. Collaboration with architects is essential.

Qualifications

• Senior AI Engineer with production AI/ML experience.
• Hands-on with LLM workflows and RAG architectures.
• Experience deploying AI in production across cloud environments.
• Strong API integration and cloud-native development skills.
• Ability to work with evolving requirements and stakeholders.

Responsibilities

• Translate AI solution concepts into production-ready implementations.
• Support delivery from POC through initial implementation and handover.
• Design, build, and deploy agentic systems and RAG workflows.
• Develop and deploy AI solutions across cloud environments (GCP preferred).
• Apply software architecture principles with security and governance in mind.
• Collaborate with solution architects and stakeholders to refine requirements.
• Work independently from technical briefs with minimal supervision.

Skills

LLM workflows

RAG architectures

API integration

GCP

AWS

Azure

SDLC

Production deployment

Cloud-native apps

Tools

GCP

AWS

Azure

Job description

D2B seeks a Senior AI Engineer to design and deploy production‑grade AI/ML systems, focusing on LLM-based workflows, RAG, and cloud platforms (GCP, AWS, Azure). You will build retrieval systems, integrate APIs, and drive AI solutions across the SDLC in a fully remote setting.

Responsibilities include translating concepts into production code, supporting from POC to handover, and ensuring scalable, secure architectures across cloud environments. Collaboration with architects is essential.