HR Business Solutions
AI / LLM Engineer
Islamabad, PKOn-siteContractFull-time
Posted Sep 18, 2026
We’re hiring an experienced AI / LLM Engineer for our UK-based client to build and optimise a production-grade, customer-facing AI assistant.
📍 Location: Islamabad
🏢 Work Mode: 100% On-site
🕐 Working Hours: UK Hours (12 PM–9 PM PKT)
Key Responsibilities
📍 Location: Islamabad
🏢 Work Mode: 100% On-site
🕐 Working Hours: UK Hours (12 PM–9 PM PKT)
Key Responsibilities
- Design and deploy scalable LLM systems for production use.
- Build and optimise RAG pipelines and knowledge retrieval systems.
- Develop embedding pipelines and work with vector databases.
- Implement fine-tuning workflows and model evaluation pipelines.
- Develop AI guardrails, policy enforcement, and escalation mechanisms.
- Optimise model performance, latency, concurrency, and GPU utilisation.
- Ensure AI systems are reliable, observable, and fully auditable.
- Integrate AI solutions with databases, APIs, and existing applications.
- Collaborate with technical, compliance, and legal teams.
- Strong production experience with Python and FastAPI or similar frameworks.
- Proven experience building and deploying LLM applications in production.
- Hands-on experience with RAG, embeddings, vector databases, and LLM APIs.
- Experience with prompt engineering, structured outputs, and AI evaluation.
- Experience with Docker, Redis, AWS, APIs, and databases.
- Understanding of LLM performance optimisation, scaling, and concurrency.
- Familiarity with open-source LLMs, vLLM, fine-tuning, or GPU deployment is a plus.
Role snapshot
Job type
Full-time
imran.tariq@hrbs.com.pk
Required skills
Production LLM system design and deploymentRAG pipeline development and knowledge retrievalEmbedding pipeline development and vector databasesModel fine-tuning workflows and evaluation pipelinesLLM performance optimization (latency, concurrency, GPU utilization)AI guardrails, policy enforcement, and escalation mechanismsObservability, reliability, and auditability for AI systemsPython development with FastAPI or similar frameworksIntegration of AI solutions with databases, APIs, and existing applicationsPrompt engineering and structured output designContainerization and infrastructure (Docker, Redis, AWS)Cross-functional collaboration with technical, compliance, and legal teamsFamiliarity with open-source LLMs and GPU deployment (vLLM, fine-tuning)
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