Senior Architect- Gen AI

As a Data Architect with Generative AI expertise, your role involves designing and implementing robust data architectures to support AI and machine learning workloads, specifically Generative AI applications. Your key responsibilities include: - Developing and optimizing data pipelines for training, validating, and deploying AI models efficiently and securely. - Integrating AI frameworks into data platforms to ensure scalability, low latency, and high throughput. - Collaborating with data scientists, AI engineers, and stakeholders to align data strategies with business goals. - Leading initiatives to ensure data governance, security, and compliance standards (e.g., GDPR, CCPA) are met in AI-driven environments. - Prototyping and implementing architectures utilizing generative models like GPT and Stable Diffusion to enhance business processes. - Staying updated with the latest trends in Generative AI, data engineering, and cloud technologies to recommend and integrate innovations. Qualifications required for this role: - A bachelor's degree in Computer Science, Data Engineering, or a related field (master's preferred). - 5+ years of experience in data architecture, with a focus on AI/ML-enabled systems. - Hands-on experience with Generative AI models such as OpenAI GPT, BERT, or similar, including fine-tuning and deployment. - Proficiency in data engineering tools and frameworks like Apache Spark, Hadoop, and Kafka. - Deep knowledge of database systems (SQL, NoSQL) and cloud platforms (AWS, Azure, GCP), including their AI/ML services like AWS Sagemaker, Azure ML, GCP Vertex AI. - Strong understanding of data governance, MLOps, and AI model lifecycle management. - Experience with programming languages such as Python or R and frameworks like TensorFlow or PyTorch. - Excellent problem-solving and communication skills, with a demonstrated ability to lead cross-functional teams. Preferred skills that would be advantageous for this role: - Familiarity with LLM fine-tuning, prompt engineering, and embedding models. - Strong domain expertise in the Life Science Industry. - Experience integrating generative AI solutions into production-level applications. - Knowledge of vector databases like Pinecone, Weaviate for storing and retrieving embeddings. - Expertise in APIs for AI models, such as OpenAI API or Hugging Face Transformers.,