AI Resume Builder
JOIN NOW Post Job
MASTER-WORKS
AI

LLM engineer

MASTER-WORKS · الرياض, S01, SA

Actively hiring Posted 4 months ago

Role overview

Master works is looking for an experienced LLM Engineer to join our team working on next-generation AI-driven analytics solutions. The ideal candidate will design and implement natural language search, semantic search solutions, and generative AI features for our web applications. You will work hands-on with advanced language models, vector databases, RAG pipelines, and build intelligent workflows to enable actionable insights from both structured and unstructured data.

Responsibilities

  • Develop and maintain natural language search capabilities and semantic search solutions using vector databases.
  • Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.
  • Build and optimize Generative AI features (summarization, recommendations, insights) for analytics applications.
  • Design and implement Agents and Workflows for complex tasks across datasets.
  • Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.
  • Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.
  • Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.
  • Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.
  • Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.
  • Bachelor's or master's degree in computer science, AI/ML, Data Science, or related field.
  • Hands-on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).
  • Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
  • Strong understanding of embeddings, semantic search, and their practical applications.
  • Expertise in RAG pipelines, Agents, and Workflow orchestration.
  • Proficiency in Python and relevant AI/ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow).
  • Familiarity with NL-to-SQL systems and natural language query processing.
  • Experience working with structured and unstructured data sources.
  • Knowledge of data pipelines, preprocessing, and storage formats for analytics.
  • Ability to design scalable, production-ready AI solutions integrated with web applications.

Preferred qualifications

  • Experience working with AI based chatbots, Natural language search, NL to SQL.
  • Knowledge of prompt engineering and fine-tuning LLMs.
  • Familiarity with data privacy, security, and compliance considerations in AI pipelines.
  • Strong problem-solving and analytical skills.
  • Excellent communication skills to work with cross-functional teams.
  • Passion for AI and staying up to date with the latest developments in LLMs and generative AI.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Ai Nlp Generative Ai
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support