Key Responsibilities 

• Data and AI Engineer responsible for Implementing AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This Includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready. 

• Real-Time Data Streaming: Build and maintain scalable and robust real-time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark streaming, or similar. 

• Develop AI-driven systems to improve data capabilities 

• Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.  

• Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc. 

• Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management. 

• Model domain entities, relationships, and business logic in knowledge graphs (e.g., Neo4j, Amazon Neptune, RDF). 

• Implement scalable semantic layer with  dynamic query translation to deliver real time insights for conversational analytics. 

• Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems. 

• Develop graph database solution for complex data relationships supporting AI systems. 

Required Skills & Experience:  

• Bachelor's degree in Computer Science, Artificial Intelligence, or related field. 

• 3+ years of data engineering experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark, Datamesh, Datalake or Data Fabric. 

• 2+ years’ experience with cloud platforms (AWS, GCP, or Azure) 

• 1+ years of data engineering experience focused on supporting AI technologies. 

• 1+ years of hands-on experience implementing AI data solutions. 

• 1+ years' experience with prompt engineering techniques for large language models. 

• 1+ years of implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models. 

• 1+ years of implementing AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph). 

• 2+ years programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow. 

• 1+ years with building AI pipelines that bring together structured, semi-structured and unstructured data.   

• 1+ years in vector databases, graph databases, NoSQL, Document DBs, including design, implementation, and optimization. (e.g., AWS open search, GCP Vertex AI, Neo4j, Spanner Graph, Neptune, Mongo, DynamoDB etc.). 

• Strong written and verbal communication skills 

• Able to communicate effectively with technical teams   

• Team player who collaborates effectively across teams   

• Strong organization and execution skills. 

• Strong interpersonal and time management skills  

• Ability to work successfully in a lean, agile, and fast-paced organization, leveraging Agile principles and ways of working.  

• Ability to translate technical topics into business solutions and strategies