Tech Stack
AWSAzureCloudDistributed SystemsETLGoogle Cloud PlatformKafkaMicroservicesPySpark
About the role
- Design, implement, and maintain scalable distributed systems, data pipelines, and ML services
- Contribute to system architecture discussions and help shape design decisions for production systems
- Build and optimize microservices and real-time inferencing solutions powering AI Agents
- Collaborate with cross-functional teams to integrate Big Data and Generative AI solutions into products and platforms such as Lakehouse, Streaming Services, and ETL Pipelines
- Write high-quality, production-ready code and participate in design reviews, code reviews, and testing
- Mentor junior engineers and contribute to engineering best practices
- Drive product vision, technical roadmap, and deliver innovations from concept to delivery
Requirements
- Degree in Computer Science, Mathematics, or a related field
- 5+ years of experience across the full software development lifecycle including design, coding, testing, deployment, and operations
- 3+ years of experience with distributed Big Data systems such as PySpark, Kafka, Lakehouse, Debezium, Druid, or Glue
- Hands-on experience delivering ML or Generative AI solutions such as RAG, AI Agents, or LLM fine-tuning in production
- Experience deploying large-scale systems on cloud platforms such as AWS, Azure, or GCP
- Strong problem-solving skills with the ability to deliver in fast-paced, collaborative environments
- Preferred: MS in Computer Science, Machine Learning, or a related field
- Preferred: Experience with Graph ML such as GNNs or Graph RAG
- Preferred: Experience in Generative AI such as RAG, Knowledge Bases, or AI Agents