Full-Stack AI Engineer

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TYPE OF WORK

Any

SALARY

N/A

HOURS PER WEEK

TBD

DATE UPDATED

Apr 10, 2026

JOB OVERVIEW

We are looking for a builder who can design, develop, and deploy production-ready AI agent systems.

This is not a research role. You will be responsible for connecting LLMs to real-world workflows (APIs, CRMs, voice systems, databases) and shipping systems that are reliable, scalable, and cost-efficient.

If your experience is primarily tutorials or prototypes without real users, this role is not a fit.

What You’ll Do
Build end-to-end AI agent systems (frontend ? backend ? LLM ? automation)
Integrate LLM APIs (OpenAI, Anthropic, etc.) into real workflows
Design and implement RAG pipelines (embeddings + vector databases)
Build and consume RESTful and WebSocket APIs
Deploy and manage systems in AWS, GCP, or Azure
Optimize for latency, cost, and reliability
Implement logging, monitoring, and production debugging
Apply security best practices (rate limiting, validation, API key handling)
Required Skills
Full-stack development (Node.js + Vite.js with React or Vue)
Python backend development (FastAPI or Flask; async preferred)
Experience with LLM APIs (prompting, embeddings, function calling)
Experience with vector databases (Pinecone, Weaviate, etc.)
Databases: PostgreSQL, MongoDB, Redis
REST + WebSocket API development
Cloud deployment (AWS, GCP, or Azure)
CI/CD and containerization (Docker; Kubernetes is a plus)
Git version control
Experience debugging production systems
AI Experience (Required)

You must have shipped at least one of the following:

AI agents (multi-step workflows, tool usage)
RAG systems (retrieval + generation)
Function calling / tool-integrated systems
LLM-based automation pipelines
What We Care About (Non-Negotiable)
You have shipped real systems used by real users
You can connect LLMs to APIs, databases, and workflows
You think in terms of automation and outcomes, not just code
You understand cost control, latency, and hallucination mitigation
You can work with incomplete requirements and figure things out
Nice to Have
LangChain, LlamaIndex, Hugging Face
Serverless (AWS Lambda, Cloud Functions)
Real-time pipelines / streaming systems
AI API cost optimization strategies

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