Artificial Intelligence Engineer

Job Title: Generative AI / LLM Engineer Role Overview We are seeking an experienced Generative AI / LLM Engineer to design, develop, and deploy advanced AI solutions leveraging large language models (LLMs) and cloud AI platforms. The ideal candidate will have deep technical expertise in AI/ML frameworks, prompt engineering, and foundation models, along with the ability to innovate and deliver enterprise-grade AI systems responsibly and ethically. Key Responsibilities Technical Execution • Design, fine-tune, and deploy Generative AI models, including LLMs (e.g., GPT, LLaMA, Claude). • Lead evaluation and integration of foundation models and APIs (e.g., OpenAI, Azure OpenAI Services). • Architect scalable and secure AI pipelines for data ingestion, training, inference, and deployment. • Build GenAI solutions on cloud platforms such as Azure OpenAI, AWS Bedrock, and GCP Vertex AI. • Implement prompt engineering, model optimization, and fine-tuning techniques for domain-specific use cases. • Leverage Python and AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, etc.) for development. Innovation & R&D • Stay updated with latest AI research in multimodal models, MLOps, and emerging LLM techniques. • Drive experimentation and POCs with new models, embeddings, and retrieval-augmented generation (RAG). • Develop internal AI copilots, agents, or productivity tools to enhance organizational efficiency and customer engagement. Governance & Ethics • Ensure explainability, fairness, and compliance with data privacy and AI ethics guidelines. • Establish monitoring systems for model drift, bias, and performance tracking in production. Required Qualifications • 10+ years in AI/ML, with 3+ years hands-on in Generative AI / LLM projects. • Proven experience with Microsoft Copilot (GitHub Copilot), Azure OpenAI Services, or AWS Bedrock. • Strong knowledge of LLMs (GPT, BERT, Claude, LLaMA, etc.) and transformer architectures. • Expertise in prompt engineering, embeddings, RAG, fine-tuning, and model optimization. • Strong programming skills in Python, with hands-on experience in ML frameworks (TensorFlow, PyTorch, Hugging Face). • Proven record of delivering enterprise-grade GenAI applications. Preferred Qualifications • Experience with multimodal AI models (text, vision, speech). • Familiarity with LangChain, Vector Databases (Pinecone, Weaviate, FAISS), and MLOps pipelines. • Strong publication/research track record in AI/ML or LLMs.