Staff Backend Engineer

Job not on LinkedIn

🕒 August 5

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🔴 Lead

🔙 Backend Engineer

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Emumba

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2011

💼 Consulting

🏢 Enterprise

🤖 Artificial Intelligence

Consulting • Enterprise • Artificial Intelligence

Emumba is an engineering and innovation partner that helps enterprises and startups design, build, and operate cloud-native systems. The company specializes in AWS cloud engineering, GenAI solutions, data platforms (cataloging, discovery, quality, and data engineering), Zero Trust security frameworks, DevOps and infrastructure automation, and enterprise-grade QA and UX. Emumba delivers production-ready, scalable, and secure enterprise applications and integrations for global clients across industries.

📋 Description

• Build backend logic for event-driven systems using message queues and pub/sub services, with strong data processing and file-handling logic • Manage concurrent tasks efficiently in distributed environments using asynchronous programming techniques • Design and implement data processing pipelines across cloud storage, compute, and database services • Optimize applications for performance and scalability through caching, async calls, and latency reduction • Design and develop serverless applications and RESTful APIs using Flask or FastAPI • Follow cloud security best practices, including IAM, encryption, and network isolation • Implement authentication mechanisms using OAuth, JWT, or managed identity services

🎯 Requirements

• 5+ years of hands-on Python backend development experience • Solid exposure to cloud-native or serverless solutions, with AWS preferred • Proven experience with distributed systems concepts, including event-driven architecture, message queues, and scalable data pipelines • Hands-on experience with asynchronous and concurrent programming • Strong testing and debugging skills across distributed architectures • Exposure to GenAI tooling or LLM-based systems, particularly RAG or agentic RAG architectures, is a plus • Experience integrating LLM APIs into backend services or workflows • Familiarity with vector databases and embedding-based search • Builder mindset; thrives on writing, debugging, and improving production code • Collaborative, humble, and open to feedback • Strong communicator who explains design decisions clearly • Influences through contribution, not hierarchy