Key Responsibilities As a Data Architect with Generative AI expertise, you will : Design and implement
robust data architectures that support AI and machine learning (ML) workloads, including Generative AI applications. Develop and optimize
data pipelines
for training, validating, and deploying AI models efficiently and securely. Integrate AI frameworks
into data platforms, ensuring scalability, low latency, and high throughput. Collaborate
with data scientists, AI engineers, and stakeholders to align data strategies with business goals. Lead initiatives to ensure
data governance , security, and compliance standards (e.g., GDPR, CCPA) are met in AI-driven environments. Prototype and implement
architectures that utilize generative models (e.g., GPT, Stable Diffusion) to enhance business processes. Stay up to date with the latest trends in Generative AI, data engineering, and cloud technologies to recommend and integrate innovations. Required Qualifications We’re looking for someone with : 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
e.g., OpenAI GPT, BERT, or similar), including fine-tuning and deployment. Proficiency in
data engineering tools and frameworks , such as Apache Spark, Hadoop, and Kafka. Deep knowledge of
database systems
SQL, NoSQL) and
cloud platforms
AWS, Azure, GCP), including their AI / ML services (e.g., 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
and frameworks like
TensorFlow
PyTorch . Excellent problem-solving and
communication skills , with a demonstrated ability to lead cross-functional teams. Preferred Skills Familiarity with
LLM fine-tuning ,
prompt engineering , and
embedding models . Strong domain expertise in Life Science Industry Experience integrating generative AI solutions into production-level applications. Knowledge of
vector databases
e.g., Pinecone, Weaviate) for storing and retrieving embeddings. Expertise in
APIs for AI models , such as OpenAI API or Hugging Face Transformers.
Senior Architect • India