<p><p><b>Responsibilities :</b><br/><br/>- Understand client business use cases and technical requirements; translate them into scalable AI architecture designs.<br/><br/></p><p>- Evaluate and propose suitable generative AI solutions using state-of-the-art models such as GPT, BERT, LLaMA, and others.<br/><br/></p><p>- Architect and develop enterprise-grade Generative AI systems using Azure AI and other cloud services (AWS, GCP, etc.
).<br/><br/></p><p>- Implement prompt engineering and Retrieval-Augmented Generation (RAG) techniques to enhance LLM performance.<br/><br/></p><p>- Design, develop, and fine-tune LLMs using frameworks such as Hugging Face Transformers, LangChain, or similar.<br/><br/></p><p>- Integrate AI solutions into enterprise platforms and APIs with a strong focus on security, scalability, and maintainability.<br/><br/></p><p>- Drive POCs to validate architecture decisions and new technologies.<br/><br/></p><p>- Collaborate with cross-functional teams to ensure high-quality delivery and alignment with non-functional requirements (NFRs).<br/><br/></p><p>- Apply CI/CD and MLOps best practices to streamline AI model deployment and monitoring.<br/><br/></p><p>- Lead architectural reviews, design documentations, and enforce design standards across AI projects.<br/><br/></p><p>- Troubleshoot and resolve technical issues through thorough root cause analysis.<br/><br/></p><p>- Stay up to date with advancements in Generative AI, LLMs, and cloud technologies.<br/><br/><b>Requirements :</b><br/><br/>- 7+ years of total experience in software development with strong exposure to AI/ML systems.<br/><br/></p><p>- Proven expertise in Generative AI and Transformer-based models (e.
g., GPT, BERT, LLaMA).<br/><br/></p><p>- Strong hands-on experience with Azure AI services and other cloud platforms (AWS, GCP).<br/><br/></p><p>- Proficient in Python and major ML libraries/frameworks like PyTorch, TensorFlow.<br/><br/></p><p>- Experience in prompt engineering, RAG pipelines, and multi-agent AI systems.<br/><br/></p><p>- Deep understanding of LLM fine-tuning, deployment, and serving pipelines.<br/><br/></p><p>- Hands-on experience with tools like Hugging Face Transformers, LangChain, and knowledge of NLP and Knowledge Engineering.<br/><br/></p><p>- Solid grasp of MLOps, CI/CD for AI, and integrating models into production environments.<br/><br/></p><p>- Strong architectural thinking with an ability to define and enforce best practices related to scalability, extensibility, security, and performance.</p><p><br/></p><p>- Excellent problem-solving skills and ability to articulate technical concepts clearly.<br/></p><br/></p> (ref:hirist.tech)