Agentic AI Systems Engineer

Faaz Tech; Karachi Division; On-site; PKR 1,800,000 - 3,600,000; Full time

Job summary

FAAZ TECH is building the next generation of intelligent software that acts on data, not just displays it. We are seeking an AI Developer who loves agentic workflows, LLM orchestration, and systems that think, plan, and execute tasks autonomously.

Join us to design robust pipelines, integrate LLMs and vector stores, optimize performance, and push the boundaries of autonomous software. If you thrive on RAG architectures and cutting-edge AI research, this is your home.

Qualifications

• 3+ years of professional software development experience.
• Strong experience with Node.js/TypeScript.
• Experience with LLM APIs and/or open-source model ecosystems.
• Understanding of RAG patterns, vector search, and prompt engineering.
• Familiar with the Agentic paradigm and self-correcting systems.
• Experience building scalable APIs connecting frontend to AI backends.
• Researcher’s mindset for debugging unpredictable AI outputs.

Responsibilities

• Agent orchestration: design and scale agentic workflows that reason and execute complex logic.
• LLM integration: leverage latest APIs and local models for advanced RAG architectures.
• System architecture: integrate AI decision-making into core business logic.
• Performance optimization: reduce latency and cost for AI features at scale.
• Data engineering: manage vector databases to provide intelligent context to our agents.
• R&D: explore LangChain, AutoGen, CrewAI to stay ahead of AI curves.

Skills

Node.js/TypeScript

LLM APIs

RAG patterns

Vector search

Prompt engineering

Agentic mindset

API design

Tools

LangChain

AutoGen

CrewAI

Pinecone/Milvus/pgvector

Job description

FAAZ TECH is building the next generation of intelligent software that acts on data, not just displays it. We are seeking an AI Developer who loves agentic workflows, LLM orchestration, and systems that think, plan, and execute tasks autonomously.

Join us to design robust pipelines, integrate LLMs and vector stores, optimize performance, and push the boundaries of autonomous software. If you thrive on RAG architectures and cutting-edge AI research, this is your home.