AI/ML Engineer

Senior

6–10 Years

Lahore, Pakistan (On-Site)

The Role

What You Will Do

• Architect and implement the full RAG (Retrieval-Augmented Generation) pipeline using Azure AI Search, with native multilingual vector indexing for both Arabic and English document corpuses — no intermediate translation layer
• Integrate Azure OpenAI Service as the primary LLM, and design the supplementary model integration layer for Sovereign AI models (Jais, Falcon) to ensure Arabic-first quality across all user-facing outputs
• Build the AI orchestration layer that routes user intents to the correct backend actions — leave submissions, ticket creation, room bookings, document generation — via a service account architecture with strict authorization guardrails
• Design and implement the prompt engineering framework, including version control, prompt registry, and audit trail for all prompts in production
• Implement confidence scoring and source attribution on all AI responses, so users and administrators can see which knowledge base article or SAP record an answer draws from
• Build the AI monitoring stack — latency dashboards, hallucination rate tracking, accuracy metrics, and bias detection — integrated with Azure Monitor and Application Insights
• Design and implement content filtering, prompt injection prevention, and adversarial input handling
• Implement conversation memory within sessions and opt-in persistent memory across sessions for the Enterprise AI Assistant
• Define and execute the model evaluation methodology, including test datasets for Arabic and English, benchmark metrics, and continuous improvement cycles
• Configure and manage token budget controls, rate limits, and graceful fallback logic when AI models are unavailable
• Collaborate with the backend team on AI service integration points, and with the frontend team on AI interaction patterns and response formatting

What We Are Looking For

• 6 to 10 years of engineering experience, with at least 3 years working directly on LLM systems, RAG pipelines, or production AI applications
• Hands-on experience with Azure OpenAI Service — model deployment, API integration, prompt management, and cost optimization
• Deep understanding of RAG architecture — chunking strategies, vector embedding models, retrieval evaluation, and re-ranking
• Experience with Azure AI Search or equivalent vector database solutions (Qdrant, Weaviate, Pinecone)
• Demonstrated work with multilingual NLP — Arabic language experience or experience with other RTL/morphologically complex languages is a strong advantage
• Proficiency in Python for AI/ML engineering — building pipelines, evaluation scripts, and production AI services
• Experience building guardrail systems — content filters, authorization enforcement in AI outputs, and adversarial input handling
• Strong grasp of AI evaluation methodology — how to measure what matters, not just what is easy to measure
• Familiarity with MLOps practices — version control for models and prompts, deployment pipelines, and monitoring in production
• Ability to communicate complex AI decisions clearly to non-technical stakeholders
• Nice to Have
• Direct experience with Arabic LLMs — Jais, Falcon, or fine-tuned Arabic variants of open-source models
• Experience with AI agent frameworks — LangChain, Semantic Kernel, or custom orchestration systems
• Background building AI systems for enterprise HR, telecom, or regulated industry environments
• Understanding of PDPL or similar data protection frameworks and their implications for AI data handling