AI Engineer

APP IN SNAP (Private) Limited

Islamabad

On-site

PKR 2,000,000 - 4,000,000

Full time

14 days+

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Benefits offered by this job

Medical Insurance

Life Insurance

Provident Fund

Professional Certifications

Training & Development Programs

EOBI

Job summary

APP IN SNAP (Private) Limited seeks a highly skilled AI Engineer to design, develop, and deploy scalable AI solutions across NLP, Computer Vision, Generative AI, and MLOps domains. The candidate will build production-grade AI systems, optimize model performance, and translate business requirements into robust AI pipelines.

Responsibilities include designing and deploying models, building RAG-based systems, end-to-end AI pipelines, and implementing safe, scalable AI services in production while

Qualifications

Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, or a related field.
3–5 years of experience in AI/ML engineering or related roles.
Experience with multi-agent systems and AI orchestration frameworks.
Knowledge of recommendation systems and ranking algorithms.
Experience in multimodal AI (vision + text + speech).
Familiarity with NL-to-SQL systems and conversational AI.
Experience with real-time AI systems and low-latency optimization.
Understanding of AI evaluation, monitoring, and explainability techniques.

Responsibilities

Design, develop, and deploy AI/ML models for real-world applications across NLP, CV, and Generative AI.
Build and optimize LLM-based systems, including RAG pipelines, embeddings, and prompt engineering frameworks.
Develop end-to-end AI pipelines, including data ingestion, preprocessing, model training, evaluation, and deployment.
Implement agentic AI systems using frameworks like LangChain, LangGraph, or similar tools.
Develop and maintain MLOps pipelines including model versioning, monitoring, CI/CD, and performance tracking.
Ensure low-latency, scalable, and reliable AI services in production environments.
Collaborate with cross-functional teams to define AI driven solutions.
Implement AI safety, guardrails, and evaluation frameworks to ensure responsible AI deployment.

Skills

Python

LLMs

Prompt engineering

Multi-agent systems

Model optimization

Education

Bachelor's or Master's in Artificial Intelligence or Computer Science

Tools

PyTorch

TensorFlow

Hugging Face

FastAPI

Docker

CI/CD

AWS

GCP

Job description

We are seeking a highly skilled AI Engineer to design, develop, and deploy scalable AI solutions across NLP, Computer Vision, Generative AI, and MLOps domains. The ideal candidate will have hands-on experience in building production-grade AI systems, optimizing model performance, and translating business requirements into robust AI pipelines.

Key Responsibilities

Design, develop, and deploy AI/ML models for real-world applications across NLP, Computer Vision, and Generative AI.
Build and optimize LLM-based systems, including RAG pipelines, embeddings, and prompt engineering frameworks.
Develop end-to-end AI pipelines, including data ingestion, preprocessing, model training, evaluation, and deployment.
Implement agentic AI systems using frameworks like LangChain, LangGraph, or similar tools. Work on recommendation systems, ranking models, and personalization engines to enhance user engagement.
Develop and maintain MLOps pipelines including model versioning, monitoring, CI/CD, and performance tracking.
Ensure low-latency, scalable, and reliable AI services in production environments.
Collaborate with cross-functional teams (product, engineering, business) to define AI driven solutions.
Implement AI safety, guardrails, and evaluation frameworks to ensure responsible AI deployment.
Optimize models for performance, cost-efficiency, and scalability.

Requirements & Qualifications

Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, or a related field.
3–5 years of experience in AI/ML engineering or related roles.
Experience with multi-agent systems and AI orchestration frameworks.
Knowledge of recommendation systems and ranking algorithms.
Experience in multimodal AI (vision + text + speech).
Familiarity with NL-to-SQL systems and conversational AI.
Experience with real-time AI systems and low-latency optimization.
Understanding of AI evaluation, monitoring, and explainability techniques.

Required Skills & Technologies

Strong programming skills in Python and experience with frameworks like PyTorch TensorFlow or Hugging Face Hands-on experience with: LLMs (OpenAI Llama etc.) RAG architectures and vector databases (Qdrant ChromeaDB Pinecone) Prompt engineering and embeddings Experience building and deploying APIs using FastAPI Django or similar frameworks Familiarity with Docker CI/CD pipelines and cloud platforms (AWS GCP) Strong understanding of data structures algorithms system design.