Senior AI Engineer

Octdaily; Pakistan; On-site; PKR 3,600,000 - 6,000,000; Full time

Job summary

Octdaily is seeking a Senior AI Engineer with 5+ years of hands-on AI/ML experience to design and deploy production-grade AI solutions. You will own LLM‑powered applications, RAG pipelines, and enterprise chatbots, collaborating across teams to deliver scalable results.

Expect deep work in NLP, computer vision, and ML pipelines, with emphasis on agentic orchestration, advanced RAG, or applied CV. This role offers impact across business units and requires strong cloud and API deployment skills.

Qualifications

• 5+ years in hands-on AI/ML engineering with production experience.
• Strong expertise in LLMs, RAG, and Generative AI development.
• Proficiency in Python and major ML/NLP frameworks.

Responsibilities

• Design, develop, and deploy large language model applications using OpenAI, Llama, and Hugging Face tools.
• Fine-tune LLMs on domain data to improve accuracy and performance.
• Build conversational AI systems and enterprise chatbots.

Skills

AI/ML engineering

LLMs

RAG

Generative AI

Python

NLP

OpenCV

Machine Learning

Distributed compute

Cloud deployment

Tools

TensorFlow

PyTorch

Keras

Scikit-learn

NLTK

spaCy

Hugging Face Transformers

OpenAI API

LangChain

LlamaIndex

Docker

AWS

Job description

We are seeking a highly skilled and innovative Senior AI Engineer with 5+ years of hands‑on experience in Artificial Intelligence, Machine Learning, Natural Language Processing, and Generative AI development. The ideal candidate has deep expertise in designing and deploying production‑grade AI solutions — including LLM‑powered applications, Agentic RAG systems, conversational AI platforms, and end‑to‑end ML pipelines — and will collaborate closely with cross‑functional teams to deliver scalable, cost‑effective, high‑impact AI solutions aligned with business objectives. This role is broad by design: candidates are not expected to be world‑class in all three specialization tracks below, but should bring strong core AI engineering skills plus demonstrated depth in at least one of Agentic Orchestration, Advanced RAG, or Applied Computer Vision.

Key Responsibilities

• Design, develop, and deploy large language model (LLM) applications using OpenAI, Llama, and Hugging Face frameworks.
• Conduct fine‑tuning of LLMs on domain‑specific and custom datasets to optimize model performance and accuracy.
• Build and deploy conversational AI systems and intelligent chatbots for enterprise use cases.

Retrieval-Augmented Generation & Agentic Systems

• Implement advanced Retrieval‑Augmented Generation (RAG) and Agentic RAG pipelines for intelligent, context‑aware AI solutions.
• Develop and extend multi‑agent AI systems using CrewAI, AutoGen, LangChain, and LlamaIndex.
• Build and extend AI workflows using Langflow and Flowise for rapid prototyping and deployment.

End-to-End Solution Architecture & Deployment

• Architect and deliver end‑to‑end AI solutions — from data preprocessing and model training to API deployment and system integration.
• Design and implement RESTful APIs using FastAPI or Flask for seamless AI component integration.
• Deploy AI systems on cloud and on‑premises infrastructure using Docker, Docker Compose, and AWS.
• Configure and optimize GPU‑accelerated environments for efficient model inference and training.
• Develop and optimize NLP pipelines including text cleaning, lemmatization, feature engineering, and advanced preprocessing.
• Design robust data preprocessing pipelines for structured and unstructured data.
• Apply advanced techniques for feature engineering, handling imbalanced datasets, and improving model accuracy.
• Build document summarization systems and text‑heavy content processing tools.

Computer Vision & OCR

• Build computer vision solutions leveraging OpenCV and deep learning frameworks.
• Implement OCR‑based document processing and data extraction systems.
• Research and evaluate emerging AI tools and frameworks for continuous innovation.
• Collaborate with cross‑functional teams to align AI solutions with business requirements.
• Present findings, ideas, and technical reports to both technical and non‑technical stakeholders.
• Prioritize open‑source tools for building cost‑effective and scalable AI solutions.

Required Skills:

• 5+ years of hands‑on AI/ML engineering experience.
• Strong expertise in LLMs, RAG, and Generative AI development.
• Proficiency in Python with TensorFlow, PyTorch, Keras, and Scikit‑learn.
• Experience with NLP frameworks — NLTK, spaCy, Hugging Face Transformers.
• Deep understanding of CNNs, RNNs, SVMs, and Neural Networks.
• Experience with Computer Vision using OpenCV.
• Proficiency with SQL/NoSQL databases — MySQL, MongoDB, Cassandra.