AI Architect

Systems Limited; Lahore; On-site; PKR 3,000,000 - 6,000,000; Full time

Job summary

Systems Limited is seeking a hands-on AI Architect to lead enterprise AI initiatives from concept to production. You will architect scalable AI systems, collaborate with stakeholders, and drive implementation of GenAI, LLMs, and RAG pipelines on Azure with CI/CD and observability.

The ideal candidate will mentor junior engineers, develop traditional ML models when needed, and ensure governance and responsible AI practices across deployments.

Qualifications

• 8+ years of experience in AI/ML engineering and solution architecture.
• 3+ years in production GenAI/LLM apps.
• Strong Python and FastAPI skills with Azure AI services.
• Experience with RAG, embeddings, vector stores, and LLM orchestration.

Responsibilities

• Lead end-to-end design, development, and deployment of AI/GenAI solutions.
• Architect scalable, secure AI systems using Azure AI services.
• Collaborate with stakeholders to translate requirements into AI solutions.
• Build and optimize LLM-powered apps, RAG pipelines, APIs, and workflows.
• Design AI solutions for document intelligence, summarization, classification, Q&A, and automation.
• Implement evaluation, observability, guardrails, and responsible AI practices.
• Optimize production AI for performance, latency, cost, and accuracy.
• Deploy applications via CI/CD, monitoring, logging, and cloud infra.
• Develop traditional ML models and mentor junior engineers while ensuring quality.

Skills

Python

FastAPI

Azure AI services

RAG

Embeddings

Vector databases

LLM orchestration

LangGraph

AutoGen

Semantic Kernel

CrewAI

NLP

Prompt engineering

Responsible AI

AI governance

CI/CD

HuggingFace

Education

Bachelor's degree in Computer Science, AI, Data Science, or related field

Master's degree preferred

Tools

LangGraph

AutoGen

Semantic Kernel

CrewAI

LangSmith

Langfuse

Azure AI Foundry

HuggingFace

Job description

We are seeking a hands-on AI Architect with extensive experience in Generative AI, Machine Learning, and Solution Architecture to design, build, and deliver enterprise-grade AI solutions. The ideal candidate will lead multiple AI initiatives from concept to production, work closely with business stakeholders, and remain actively involved in implementation. This role requires expertise in LLMs, RAG architectures, Azure AI services, AI governance, evaluation frameworks, and scalable cloud-based deployments.

Key Responsibilities:

• Lead the end-to-end design, development, and deployment of AI and GenAI solutions.
• Architect scalable, secure, and high-performance AI systems using Azure AI services.
• Collaborate with business and client stakeholders to translate requirements into AI solutions.
• Build and optimize LLM-powered applications, RAG pipelines, APIs, and AI workflows.
• Design AI solutions for document intelligence, summarization, classification, Q&A, and automation.
• Implement AI evaluation, observability, guardrails, and responsible AI practices.
• Optimize production AI systems for performance, latency, cost, and accuracy.
• Deploy AI applications using CI/CD, monitoring, logging, and cloud infrastructure.
• Develop traditional ML models where required and mentor junior engineers while ensuring solution quality.

Qualifications:

• 8+ years of experience in AI/ML engineering and solution architecture.
• 3+ years of hands-on experience building production-grade GenAI and LLM applications.
• Strong expertise in Python, FastAPI, Azure AI services, RAG, embeddings, vector databases, and LLM orchestration frameworks.
• Experience with AI agents (LangGraph, AutoGen, Semantic Kernel, CrewAI), AI evaluation (RAGAS, BLEU, Precision, Recall, F1), and observability tools (LangSmith, Langfuse, Azure AI Foundry).
• Solid understanding of NLP, prompt engineering, responsible AI, guardrails, model evaluation, and AI governance.
• Experience deploying AI solutions on Azure with CI/CD, monitoring, and hybrid cloud/on-premise architectures.
• Experience with HuggingFace, open-source LLMs, and enterprise AI deployments.
• Bachelor's degree in Computer Science, AI, Data Science, or a related field (Master's preferred).

Preferred:

• Experience with open-source LLMs (LLaMA, Mistral, Qwen, DeepSeek).
• Exposure to AWS Bedrock or GCP Vertex AI.
• Experience with multilingual NLP (especially Arabic).
• Microsoft Azure certifications (AI-102, DP-100, AZ-305).