<p>We are seeking a highly skilled and innovative Senior Full- Stack AI / LLM Engineer to join our team and lead the development of cutting-edge AI solutions. This role focuses on building intelligent systems using large language models (LLMs), generative image models, and multimodal AI technologies. You will work across the stack—from model integration and orchestration to deployment and automation—helping us deliver scalable, production-grade AI applications.</p><p><br></p><p>Key Responsibilities</p><ul><li>Design, develop, and deploy Python-based microservices and APIs for AI-powered applications.</li><li>Integrate and fine-tune LLMs from providers such as OpenAI, Anthropic, Meta, and Mistral.</li><li>Build Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain or LlamaIndex.</li><li>Implement semantic search and vector database solutions using Pinecone, Weaviate, Chroma, Milvus, or Supabase.</li><li>Develop and integrate TTS/STT systems using tools like OpenAI Whisper, Coqui TTS, and ElevenLabs.</li><li>Work with generative image models including GPT-Image-1, Stable Diffusion, and ComfyUI.</li><li>Automate workflows using orchestration platforms such as n8n, Make, or Zapier.</li><li>Deploy AI services on cloud platforms (GCP, AWS, or Azure) with scalability and reliability in mind.</li><li>Apply prompt engineering best practices to optimize model performance and output quality.</li><li>Collaborate with cross-functional teams including product, design, and data science to deliver impactful AI features.</li></ul>

<p>Required Qualifications:</p><ul><li>Strong proficiency in Python and experience building APIs, microservices, and automation scripts.</li><li>Hands-on experience with LLMs and generative AI tools from major providers.</li><li>Deep understanding of RAG architectures and experience implementing them in production.</li><li>Familiarity with LangChain, LlamaIndex, or similar frameworks.</li><li>Experience with vector databases and semantic search techniques.</li><li>Knowledge of TTS/STT systems and their integration into conversational or multimodal applications.</li><li>Experience with generative image models and related tooling.</li><li>Proficiency in automation platforms like n8n, Make, or Zapier.</li><li>Cloud deployment experience on GCP, AWS, or Azure.</li><li>Strong grasp of prompt engineering principles and techniques.</li></ul><p>Preferred Qualifications</p><ul><li>Experience with fine-tuning or customizing LLMs.</li><li>Familiarity with containerization (Docker) and orchestration (Kubernetes).</li><li>Background in machine learning, NLP, or computer vision.</li><li>Contributions to open-source AI projects or communities.</li></ul>

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