Full-Stack & Agentic AI Engineer

VaporVM; Lahore; On-site; PKR 1,800,000 - 3,600,000; Full time

Job summary

VaporVM in Lahore is seeking an AI Engineer with a solid full-stack background to design, develop, and deploy production-grade AI applications and agentic systems. The role combines hands-on full-stack development with practical experience in LLMs, RAG, AI agents, and data pipelines to deliver scalable solutions across cloud and containerized environments.

You will collaborate with product and data teams to translate requirements into production-ready AI capabilities, focusing on performance,

Qualifications

• Experience building full-stack AI-enabled applications.
• Hands-on with LLMs and Generative AI.
• Knowledge of RAG, embeddings, vector databases and retrieval pipelines.
• Experience deploying AI agents in production.
• Strong API design and microservices architecture.

Responsibilities

• Design and develop AI-powered applications and agentic solutions using modern LLM technologies.
• Build scalable full-stack applications including backend APIs, services, databases, and frontends.
• Develop RAG pipelines with vector databases, embeddings, processing, and retrieval.
• Build and orchestrate AI agents capable of reasoning, tool usage, and multi-step workflows.
• Work with LLMs, prompt engineering, context management, function/tool calling, and agent orchestration.
• Integrate AI models via APIs and frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel.

Skills

Full-stack development

Python

Node.js

Frontend React/Next.js

REST APIs

LLMs

RAG

AI agents

Prompt engineering

Data pipelines

Tools

Docker

Kubernetes

CI/CD

Cloud platforms

Job description

We are looking for a strong AI Engineer with a solid full-stack software engineering background to design, develop, and deploy production-grade AI applications and intelligent agentic systems.

The ideal candidate should combine hands-on full-stack development expertise with practical experience in LLMs, RAG, AI agents, orchestration frameworks, APIs, and data pipelines. Candidates who have actually built and deployed AI agents in production will be strongly preferred.

Key Responsibilities

• Design and develop AI-powered applications and agentic solutions using modern LLM technologies.
• Build scalable full-stack applications, including backend APIs, services, databases, and frontend interfaces.
• Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases, embeddings, document processing, and retrieval techniques.
• Build and orchestrate AI agents capable of reasoning, tool usage, task execution, and multi-step workflows.
• Work with LLMs, prompt engineering, context management, function/tool calling, and agent orchestration.
• Integrate AI models and services through APIs and frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.
• Design and implement data pipelines for ingestion, transformation, processing, indexing, and retrieval.
• Develop secure and scalable APIs and microservices to integrate AI capabilities with enterprise applications.
• Deploy and operate AI solutions across cloud and containerized environments.
• Optimize AI applications for performance, scalability, reliability, latency, and cost.
• Implement evaluation, monitoring, logging, and observability for LLM and agentic applications.
• Collaborate with product, engineering, data, and business teams to translate requirements into production-ready AI solutions.

Required Skills & Experience

• 5+ years of software/full-stack engineering experience with strong hands-on development expertise.
• Strong proficiency in Python and/or Node.js.
• Solid experience with modern frontend technologies such as React, Next.js, or equivalent.
• Strong backend/API development experience using REST APIs, microservices, and databases.
• Practical experience building applications using LLMs and Generative AI.
• Strong understanding of RAG, embeddings, vector databases, semantic search, and retrieval pipelines.
• Experience with AI agent development and orchestration frameworks.
• Hands-on experience with LLM APIs, tool/function calling, prompt engineering, and structured outputs.
• Experience with data pipelines, ETL/ELT, data ingestion, and data processing is highly desirable.
• Experience with Docker, Kubernetes, CI/CD, Git, and cloud platforms.
• Strong understanding of software architecture, security, scalability, and production deployment.

Strongly Preferred

• Proven experience building and deploying AI agents into production.
• Experience with multi-agent architectures and agentic workflows.
• Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
• Experience with Azure AI, AWS Bedrock, Google Vertex AI, OpenAI, or equivalent platforms.
• Experience with Kafka, Spark, Airflow, Databricks, or similar data technologies.
• Experience implementing LLM evaluation, observability, guardrails, and AI security.