Python Backend Engineer

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What You’ll Do

• Own backend system architecture for a high-throughput, real-time analytics platform. 
• Lead the design and development of secure REST APIs and microservices in Python. 
• Architect and integrate GenAI workflows using LlamaIndex, LangChain or similar frameworks. 
• Implement real-time streaming using Server-Sent Events (SSE), event-driven patterns, and messaging systems. 
• Optimize and maintain database architectures (SQL/NoSQL) for performance and scalability. 
• Define and enforce security best practices, authentication, and authorization (OAuth2, JWT). 
• Establish standards for structured logging, monitoring, and distributed tracing. 
• Drive cloud-native deployments and ensure systems scale seamlessly. 
• Mentor mid-level engineers, lead architecture discussions, and set engineering standards. 
• Collaborate across product, data, and infrastructure teams to align backend capabilities with business needs.   

Must-Have Skills

• 3–7 years of professional Python backend development experience 
• Expert in REST API design and microservices architecture 
• Strong proficiency with security best practices for backend systems 
• SSE, WebSockets, and event-driven architecture experience 
• Strong database skills: PostgreSQL/MySQL, MongoDB, or other NoSQL systems 
• Authentication & authorization (OAuth2, JWT), RBAC 
• Proven experience leading technical discussions and mentoring developers  

Preferred Skills (Nice-to-Haves)

• Exposure to MCP, A2A is a big plus. 
• Hands-on experience with LlamaIndex, LangChain, or similar AI tooling is a big plus. 
• Logging, monitoring, and tracing (ELK, Prometheus, Grafana, OpenTelemetry) 
• AWS cloud services (EC2, Lambda, S3, API Gateway) 
• Kubernetes orchestration (EKS preferred) 
• CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) 
• Infrastructure-as-Code (Terraform, CloudFormation) 
• Messaging systems (Kafka, RabbitMQ, AWS SNS/SQS) 
• Caching strategies (Redis, Memcached) 
• Containerization (Docker) and image optimization 
• Serverless computing patterns 
• Matplotlib or backend-driven chart generation 
• Performance profiling and load testing tools (Locust, JMeter)

Note:

Why You’ll Love This Role

• Impact – You’ll design the systems that power critical analytics for thousands of users. 
• Challenge – Build and scale real-time, secure APIs in a high-performance environment. 
• Innovation – Lead the integration of advanced GenAI capabilities into large-scale backend systems.