A high-performance RAG-based platform designed to handle complex queries over financial reports, legal documents, and academic papers.
The goal is to rebuild the existing RAG system into a fully stateless, cloud-native architecture that can scale seamlessly on AWS Fargate/ECS. You’ll join a small, highly skilled engineering team and work closely with senior leadership to design, optimize, and scale a next-generation data retrieval solution.
Talent You’ll Bring Into Our Team: * 5+ years of hands-on experience in backend development using Python * Strong expertise with FastAPI and modern backend architecture principles * Proven experience with AWS services (Fargate, ECS, scaling policies, observability) * Background in distributed systems and queue-based architectures * Experience designing and building RESTful APIs and modular service components * Solid understanding of data ingestion pipelines and scaling strategies * Familiarity with monitoring tools like CloudWatch, Prometheus, Grafana * Upper-Intermediate or higher level of English for daily communication
Responsibilities: * Design and implement scalable, stateless backend services using Python (FastAPI) * Improve ingestion & structured extraction reliability by implementing better key management, throttling, and retry strategies * Develop unit and integration tests for FastAPI management APIs, ensuring complete coverage and stability * Automate worker auto-scaling by managing AMI builds, launch templates, and scaling policies within AWS * Build solutions for parallelizing massive extraction jobs using optimized queue management and orchestration strategies * Integrate monitoring and observability tools to track worker utilization, queue status, and infrastructure health * Collaborate with senior engineers and leadership on architectural planning and decision-making * Ensure clean, maintainable, and testable code with CI/CD integration
Nice to Have: * Experience with RAG systems, LLMs, or semantic search * Familiarity with high-performance data retrieval engines * Knowledge of parallelized pipelines and advanced data processing techniques
Benefits program: * Paid vacation, paid sick leaves, 10 Public holidays, additional days off * Educational budget and support in receiving certificates/attending conferences, etc. * English lessons
Comfortable Working conditions: * Flexible working hours * Amortization program or provision of required equipment
