Principal GenAI Engineer: Enterprise Backend & LLM Systems

Globespan; Washington (District of Columbia); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Turing is seeking a Principal GenAI Engineer to lead enterprise-scale AI implementations for Fortune 500 clients. You will design and build scalable, production-grade GenAI systems powered by LLMs, RAG, and agent-based architectures in a hybrid Washington DC setting.

The role sits at the intersection of backend/fullstack engineering and applied AI, building reliable systems that tightly integrate LLM capabilities into real-world applications for large organizations.

Qualifications

• 8–14 years of software engineering experience.
• 2+ years with LLMs (RAG, agents, prompt engineering).
• Experience building production-grade distributed systems.
• Proficiency in Python.
• Experience with SQL and NoSQL databases.
• Experience deploying systems on AWS / Azure / GCP and APIs/microservices.

Responsibilities

• Design and build scalable GenAI applications using LLMs and RAG pipelines.
• Develop and optimize backend services and APIs for AI-powered systems.
• Build and deploy agent-based workflows and orchestration systems.
• Integrate LLMs into real-world enterprise applications.
• Ensure performance, scalability, and reliability of AI systems in production.
• Collaborate with product, data, and engineering teams to deliver end-to-end solutions.
• Implement monitoring, evaluation, and guardrails for GenAI systems.

Skills

Software engineering

LLMs experience

Python

APIs and microservices

System design

Cloud deployment (AWS/Azure/GCP)

Tools

LangChain

LangGraph

Pinecone

Weaviate

FAISS

AWS

Azure

GCP

React

Next.js

Job description

Turing is seeking a Principal GenAI Engineer to lead enterprise-scale AI implementations for Fortune 500 clients. You will design and build scalable, production-grade GenAI systems powered by LLMs, RAG, and agent-based architectures in a hybrid Washington DC setting.

The role sits at the intersection of backend/fullstack engineering and applied AI, building reliable systems that tightly integrate LLM capabilities into real-world applications for large organizations.