Senior AI Engineer

Xceed appears to be involved in software development, particularly focusing on application and AI/ML technologies with a focus on .NET frameworks.

CRITICAL REQUIREMENTS: Minimum 2+ years of hands-on commercial experience specifically building, fine-tuning, and deploying LLM, Generative AI, and RAG pipelines in production environments is mandatory. Strong, professional proficiency in Python is mandatory. Fresh graduates, prompt-only hobbyists, and applicants without production LLM/RAG experience will be automatically filtered out. About the Role: We are seeking an advanced Senior AI Engineer (LLM & Generative AI) to architect, build, scale, and optimize state-of-the-art AI-powered applications, vector search solutions, and RAG pipelines. Key Responsibilities: Architect, develop, and maintain robust production-grade AI and LLM-powered applications. Build, fine-tune, and optimize Retrieval-Augmented Generation (RAG) pipelines, semantic search solutions, and vector embeddings. Seamlessly integrate foundation models (OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock) into scalable backend systems. Continuously evaluate AI performance, reduce latency, optimize token costs, and refine prompt engineering. Ensure data security, reliability, and high throughput across all cloud AI deployments. Requirements & Qualifications: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field. 2+ years of hands-on experience building and deploying AI/LLM solutions in production. Strong proficiency in Python (C# / .NET background is a major plus). Practical experience leveraging major foundation models and cloud platforms (OpenAI, Azure OpenAI, Anthropic, Bedrock). Deep understanding of RAG architectures, vector databases, embeddings, and vector search mechanisms. Familiarity with modern AI frameworks (e.g., LangChain, LlamaIndex) and infrastructure tools. Fluent in English (written and spoken). Show more

A senior AI engineer specializes in designing, developing, and maintaining advanced artificial intelligence systems. They collaborate with cross-functional teams to integrate machine learning models into production environments.