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Metro senior backend role with specialized document/LLM skills attracts experienced candidates, moderate applicant density.
Medium — backend, cloud, and streaming skills transfer well, but document/LLM and DynamoDB specificity restricts fit.
High — explicit 7–10 years plus many mandatory cloud, data, and infra tech requirements.
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Design, develop, and maintain scalable data pipelines and microservices primarily in Python, handling millions of documents through intelligent document processing.
Integrate advanced AI/ML technologies including LLMs, Langgraph, and Prompt Engineering to build AI-driven solutions.
Architect and deploy high-scale cloud-native services on AWS, leveraging NoSQL (DynamoDB), Kafka streaming, and ensuring system optimization and scalability.
7 to 10 years of professional software development experience in a product-based company with rapid scaling.
Expert-level proficiency in Python and Java.
Experience with document parsing and data extraction from structured/unstructured formats (PDFs, HTML, XML).
Strong hands-on experience with NoSQL databases (DynamoDB), Kafka or similar messaging systems, AWS cloud services, and Infrastructure as Code tools (K8s, CDK, Terraform, or CloudFormation).
Experienced in designing and operating distributed microservices and event-driven architectures in cloud-native environments.
Proficient in building robust data engineering pipelines at scale with deep familiarity in document processing and AI/ML tool integration.
Capable of leading technical decisions, troubleshooting complex systems, and mentoring engineering teams in a fast-paced, ambiguous environment.