Senior AI LLM Architect Onsite Lahore Fulltime

Position: Senior AI LLM ArchitectJob Type: FTELocation: Onsite Role – Lahore Office Job SummaryWe are seeking a highly skilled Senior AI LLM Architect to lead the design, development, and integration of advanced AI-driven systems using Large Language Models (LLMs). This role blends deep expertise in AI/ML engineering with strong front-end architecture capabilities to create intelligent, responsive, and user-centric products. The ideal candidate will be passionate about applying AI to real-world applications, bridging data science with modern software engineering, and ensuring performance, scalability, and usability across the product lifecycle.You will serve as the technical anchor for all AI-powered initiatives—designing robust architectures, fine-tuning LLMs for contextual accuracy, and seamlessly integrating them with modern front-end frameworks. Responsibilities1. LLM Integration and Optimization• Design, fine-tune, and deploy Large Language Models (LLMs) aligned with product and business objectives.• Implement prompt engineering, RAG (Retrieval-Augmented Generation) pipelines, and context-aware AI workflows.• Optimize model inference, latency, and response quality through model compression, quantization, or distributed serving.• Collaborate with data scientists to evaluate and benchmark models using real-world datasets.2. Front-End Architecture and Development• Architect and develop scalable, performant, and responsive front-end applications using React.js, Next.js, TypeScript, and Tailwind CSS.• Integrate AI-driven components (chatbots, summarizers, recommendations) into the user interface with a strong focus on UX.• Ensure smooth interoperability with backend systems through REST APIs and GraphQL.• Maintain code quality, reusable components, and accessibility standards across platforms. 3. AI-Powered Feature Implementation• Lead the implementation of AI-enhanced product features such as conversational assistants, intelligent dashboards, auto-summarization tools, and knowledge retrieval systems.• Collaborate with cross-functional teams (ML, backend, design, product) to conceptualize and deliver new AI functionalities.• Translate business requirements into scalable, maintainable AI-enabled front-end solutions.4. Performance and User Experience Tuning• Optimize front-end performance, loading times, and model response latency to deliver a frictionless user experience.• Implement real-time analytics, monitoring, and A/B testing for AI feature performance.• Ensure security, reliability, and compliance in all deployed AI-driven applications.5. Cross-Team Collaboration• Partner with backend engineers to integrate AI APIs, vector databases, and CI/CD workflows.• Work closely with ML engineers on data ingestion, model training pipelines, and inference endpoints.• Collaborate with UI/UX teams to refine user journeys for AI interaction.• Contribute to internal documentation, knowledge sharing, and mentoring of junior engineers. Skills & Experience• 5 - 8 years of experience of designing, development and integration of advanced AI-driven systems.• Proficiency in PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and OpenAI APIs.• Hands-on experience in fine-tuning LLMs, prompt optimization, and RAG pipeline development.• Strong understanding of NLP, embeddings, tokenization, and model serving.• Advanced proficiency in React.js, Next.js, TypeScript, Redux, and Tailwind CSS.• Experience in integrating AI-driven functionalities within web and mobile interfaces.• Solid understanding of frontend performance optimization, accessibility, and UX principles.• Familiarity with Docker, GitHub Actions, REST APIs, GraphQL, and CI/CD pipelines.• Experience with containerized deployments and cloud-based hosting (AWS, GCP, or Azure).• Preferred: Experience with RAG pipelines using vector databases like Pinecone, FAISS, or Weaviate.• Preferred: Exposure to observability tools for monitoring AI-driven applications (Prometheus, Grafana).• Preferred: Understanding of secure AI deployment practices and data privacy compliance (GDPR, SOC2).• Excellent communication and collaboration abilities across technical and non-technical teams.• Proven experience in AI project lifecycle management—from concept to deployment.• Demonstrated leadership in mentoring developers or leading cross-functional AI initiatives. Qualifications & Certifications• Bachelor’s degree in computer science, AI/ML, Data Engineering, or a related field.• Certifications (Preferred):o AWS Certified Machine Learningo Google Cloud Professional Machine Learning Engineero Microsoft Certified: Azure AI Engineer Associateo TensorFlow Developer Certificate