
AI Engineer for Golang Systems & AI Automation – UK/USA
About Our Engineers
An expert in backend design and AI orchestration, this engineer writes battle-tested Golang code, automates workflows, and powers AI features with maximum efficiency. Their work is trusted by scaling startups and enterprise teams across finance, health, and SaaS domains.
Key Expertise & Skills
Golang Development
AI-Powered Automation
GPT API Integration
NLP Workflows
LLM Application Layer
Realtime Systems
Streaming Data Architecture
Serverless Engineering
Technologies & Tools
Go
OpenAI GPT-4
LangChain
Docker
Kubernetes
Google Cloud
AWS Lambda
Redis
PostgreSQL
NATS
FastAPI
Hugging Face
REST/gRPC
Projects Our Engineers Have Worked On
- Multi-Model GPT Router in Go – Designed a backend system that intelligently routes between GPT-3.5, GPT-4, and Claude APIs based on token size, user tier, and load; deployed in production for a global productivity platform.
LLM-Based Support Agent on Go Backend – Built a smart assistant powered by GPT, running on Go with gRPC; reduced average ticket response time from 6 hours to under 20 minutes.
Real-Time Analytics Engine for ML Output – Created a Kafka + Go pipeline that processes incoming model predictions, aggregates results, and updates dashboards with <2s delay across 30+ concurrent streams.
Healthcare NLP Engine Using GPT – Built a Go-based API that processes patient text notes through GPT-4 to generate diagnostic summaries, treatment suggestions, and ICD codes for hospital EMR integration.
LLM-Powered Document Tagging System – Developed a distributed Go service that tags, classifies, and stores legal documents using OpenAI and Pinecone embeddings with role-based access control.
Event-Driven AI Copilot System – Architected a complete backend that listens to event streams from product teams, routes requests to GPT/Whisper models, and syncs AI responses with Notion + Slack using Go routines.
Who Should Hire This Engineer?
VC-funded startups building AI infrastructure
Enterprises scaling Golang-based tools
Product teams requiring real-time AI pipelines
SaaS apps using LLMs in production
CTOs looking to modernize backend and ML integration