Job VC

We are looking for a Senior Data Engineer who can design, implement, and evolve scalable data systems in
AWS
.
Core Responsibilities

Design and implement batch and streaming data pipelines using
Apache Spark.
Build and evolve a scalable
AWS-based data lake architecture.
Develop and maintain
real-time data
processing systems (event-driven pipelines).
Own performance tuning and cost optimization of
Spark workloads.
Define best practices for
data modeling, partitioning, and schema evolution.
Implement monitoring, observability, and data quality controls.
Contribute to
infrastructure automation
and
CI/CD
for data workflows.
Participate in architectural decisions and
mentor
other engineers.
R
Requirements
5+ years of commercial experience as a Data Science / AI Engineer
Strong Python skills and solid software engineering fundamentals
Proven experience building high-load, production-grade systems
2+ years of experience working with LLM and NLP-related tasks
Hands-on experience with RAG pipelines and vector databases
Strong understanding of modern deep learning architectures
Experience with at least one deep learning framework (TensorFlow or PyTorch)
Experience with SQL and NoSQL databases
Good knowledge of Kubernetes
Experience working with modern AI development tools (e.g., Claude Code, Cursor)
Upper-Intermediate or higher level of English (spoken and written)
Familiarity with Model Context Protocol (MCP)
Experience with production LLM frameworks (e.g., vLLM)
Experience training or fine-tuning LLMs
Experience with cloud platforms (AWS, Google Cloud, Azure)
Participation in Kaggle or similar competitions