Senior Manager- GenAI Architect

Job description

**About the Role** We are looking for an experienced and visionary **Generative AI Architect** with 1116 years of experience in AI/ML, including hands-on work with **LLMs (Large Language Models)** and **Generative AI solutions**. In this strategic technical leadership role, you will be responsible for designing and overseeing the development of advanced GenAI platforms and solutions that transform business operations and customer experiences. As the GenAI Architect, you will work closely with data scientists, ML engineers, product teams, and stakeholders to conceptualize, prototype, and scale generative AI use cases across the organization or client engagements. **Key Responsibilities** **GenAI Solution Architecture & Design** - Lead the design and development of scalable **GenAI solutions** leveraging **LLMs**, **diffusion models**, and **multimodal architectures**. - Architect end-to-end pipelines involving **prompt engineering**, **vector databases**, **retrieval-augmented generation (RAG)**, and **LLM fine-tuning**. - Select and integrate foundational models (e.g., **GPT, Claude, LLaMA, Mistral**) based on business needs and technical constraints. **Technical Strategy & Leadership** - Define **GenAI architecture blueprints, best practices, and reusable components** for rapid development and experimentation. - Guide teams on **model evaluation, inference optimization**, and **cost-effective scaling strategies**. - Stay current on the rapidly evolving GenAI landscape and assess emerging tools, APIs, and frameworks. **Collaboration & Delivery** - Work with product owners, business leaders, and data teams to identify **high-impact GenAI use cases** across domains like customer support, content generation, document understanding, and code generation. - Support **PoCs, pilots, and production deployments** of GenAI models in secure, compliant environments. - Collaborate with MLOps and cloud teams to enable **continuous delivery, monitoring, and governance** of GenAI systems. **Required Qualifications & Experience** - **Education:** Bachelor's or Master’s degree in **Computer Science, Artificial Intelligence, Data Science, or related technical field**. PhD is a plus. - **Experience:** 12–15 years in AI/ML and software engineering, with **3+ years focused on Generative AI and LLM-based architectures**. **Core Skills** - Deep expertise in **machine learning**, **natural language processing (NLP)**, and **deep learning architectures**. - Hands-on experience with **LLMs, transformers, fine-tuning techniques (LoRA, PEFT)**, and **prompt engineering**. - Proficient in **Python**, with libraries/frameworks such as **Hugging Face Transformers, LangChain, OpenAI API, PyTorch, TensorFlow**. - Experience with **vector databases** (e.g., Pinecone, FAISS, Weaviate) and **RAG pipelines**. - Strong understanding of **cloud-native AI architectures** (AWS/GCP/Azure), containerization (Docker/Kubernetes), and API integration. **Architectural & Leadership Skills** - Proven ability to design and deliver **scalable, secure, and efficient GenAI systems**. - Strong communication skills for cross-functional collaboration and stakeholder engagement. - Ability to mentor engineering teams and drive innovation across the AI/ML ecosystem. **Nice-to-Have** - Experience with **multimodal models** (text + image/audio/video). - Knowledge of **AI governance, ethical AI, and compliance frameworks**. - Familiarity with **MLOps practices for GenAI**, including model versioning, drift detection, and performance monitoring.