Artificial Intelligence Engineer - Exper Labs

taraki-search; Lahore; On-site; PKR 2,400,000 - 6,000,000; Full time

Job summary

Exper Labs in Lahore seeks an AI Engineer with 3–6 years of software experience to build AI agents using LLMs and RAG. You will design prompts, integrate major LLM APIs, and develop FastAPI microservices that orchestrate agent workflows in a containerized environment.

You will work with Pinecone/FAISS for context-aware interactions, apply prompt engineering, and contribute to in-house model training and optimization initiatives as the platform evolves.

Qualifications

• 3–6 years of hands-on software engineering in AI/ML systems.
• Experience integrating external LLMs (OpenAI, Anthropic, Google).
• Strong prompts design and effective LLM interactions.
• Proficiency with Python and FastAPI for RESTful APIs.
• Experience with RAG implementations and vector databases.
• Cloud familiarity (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Foundational ML knowledge; exposure to PyTorch, TensorFlow, or Hugging Face.
• Strong problem solving, communication, and Agile teamwork.
• Bachelor's or Master's in Computer Science, AI, or related.

Responsibilities

• Architect, build, test, and maintain AI agents in FastAPI services.
• Integrate with LLM APIs; design prompts for retail use cases.
• Implement RAG with vector databases to enrich interactions.
• Develop scalable microservices to manage agent logic and LLMs.
• Prepare data for prompt context and potential model fine-tuning.
• Collaborate with product and engineering teams on AI features.

Skills

Python

FastAPI

LLM integration

Prompt engineering

RAG

Docker

Kubernetes

Cloud platforms

Agile

Education

Bachelor's or Master's in CS/AI

Tools

Pinecone

FAISS

PyTorch

TensorFlow

Hugging Face

Job description

Our client Exper Labs is looking for Artificial Intelligence Engineer in Lahore.

Job Description

Position Overview

We're looking for a skilled AI Engineer with 3–6 years of experience in building intelligent applications powered by Large Language Models (LLMs). This role centers around developing AI Agents for our platform, with a focus on integrating third‑party LLM APIs (such as OpenAI, Anthropic, and Google) using advanced prompt engineering and RAG (Retrieval-Augmented Generation) techniques. You'll be working primarily with Python and FastAPI, designing logic that empowers these agents to handle complex workflows in the e-commerce and retail data space.

What You’ll Do

• Develop AI Agents: Architect, build, test, and maintain the core logic behind our AI agents within FastAPI‑based services. Manage agent state, orchestrate tasks, integrate with platform data, and leverage LLM capabilities.
• LLM Integration & Prompt Design: Work with APIs from major LLM providers, crafting and iterating on prompts tailored to retail use cases like summarization, Q&A, and content generation.
• Implement RAG Solutions: Use vector databases (e.g., Pinecone, FAISS) to enrich LLM interactions with relevant context through Retrieval‑Augmented Generation techniques.
• Build FastAPI Services: Develop scalable FastAPI microservices to serve and manage agent logic, LLM interactions, and platform‑level workflows within containerized environments (Docker, Kubernetes).
• Data Preparation: Process and curate data to support prompt context, RAG pipelines, and potentially model fine‑tuning in the future.
• Collaborate Across Teams: Partner with product and engineering teams to deliver AI features and continuously adapt to advancements in the LLM ecosystem. Be ready to contribute to in‑house model training and optimization efforts as we grow.

What You Bring

• 3–6 years of hands‑on software engineering experience, with a solid focus on AI or ML‑based systems.
• Experience integrating external LLMs (OpenAI, Anthropic, Google, etc.) into real‑world applications.
• Strong skills in prompt engineering and designing effective interactions with LLMs.
• Proficiency in Python and familiarity with FastAPI for building robust RESTful APIs.
• Practical knowledge in architecting AI‑powered features, workflows, or autonomous agents.
• Hands‑on experience with RAG implementations and vector databases like Pinecone or FAISS.
• Foundational understanding of ML principles and exposure to tools like PyTorch, TensorFlow, or Hugging Face.
• Comfortable working with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
• Strong analytical mindset and communication skills.
• Familiar with Agile development methodologies and remote collaboration.
• Eager to grow in the AI space and contribute to future innovations in LLM training and deployment.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related discipline.