AI API & LLM Solutions Engineer

Gigalabs; Lahore; On-site; PKR 2,411,000 - 2,678,000; Full time

Job summary

Gigalabs in Lahore is seeking an experienced backend engineer to build AI-driven APIs and data pipelines. You will implement FastAPI/Flask services, manage PostgreSQL databases, and optimize for performance and reliability.

You'll work with LangChain and OpenAI APIs, design robust prompts, and automate data workflows with n8n, ETL/ELT processes, and vector data techniques for RAG use cases.

Qualifications

• Advanced Python for data manipulation and backend logic.
• Experience building, documenting, and maintaining RESTful APIs with FastAPI and Flask.
• Ability to wrap data models and scripts into deployable microservices.
• Experience constructing LLM pipelines with LangChain, LlamaIndex, or custom scripts.
• Deep familiarity with OpenAI APIs and cost optimization strategies.
• Proven prompt engineering to yield structured JSON outputs from unstructured data.
• Advanced SQL with PostgreSQL and performance tuning; vector data and RAG tooling.
• Data modeling for historical data and LLM interaction logs.
• Strong n8n workflow automation for complex integrations; ETL/ELT pipelines.

Responsibilities

• Develop AI-driven APIs and internal tools using FastAPI that serve data insights.
• Automate business logic with autonomous n8n workflows.
• Ensure data quality for inputs and outputs of LLM pipelines.
• Maintain and optimize PostgreSQL for relational and vector data workloads.

Skills

Python proficiency

API development

Microservices

LLM pipelines

OpenAI API

Prompt engineering

PostgreSQL mastery

Vector data (pgvector)

Data modeling

n8n workflow automation

ETL/ELT with Python

Tools

FastAPI

Flask

LangChain

LlamaIndex

pgvector

Job description

Gigalabs in Lahore is seeking an experienced backend engineer to build AI-driven APIs and data pipelines. You will implement FastAPI/Flask services, manage PostgreSQL databases, and optimize for performance and reliability.

You'll work with LangChain and OpenAI APIs, design robust prompts, and automate data workflows with n8n, ETL/ELT processes, and vector data techniques for RAG use cases.