Python Backend Engineer

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Why This Role Matters

As our Python Backend Engineer, you will own and evolve the backend architecture for a large-scale analytical platform that processes massive datasets and serves thousands of concurrent users inreal time.

You’ll design low-latency, secure, and reliable APIs, lead the integration of GenAI-powered workflows, and ensure our system meets the highest standards of performance, scalability, and resilience.

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 microservice 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
• Hands-on experience with LlamaIndex, LangChain, or similar AI tooling
• Strong database skills: PostgreSQL/MySQL, MongoDB, or other NoSQL systems
• Authentication & authorization (OAuth2, JWT)
• Logging, monitoring, and tracing (ELK, Prometheus, Grafana, OpenTelemetry)
• Proven experience leading technical discussions and mentoring developers

Preferred Skills (Nice-to-Haves)

• Exposure to MCP, A2A is a big plus.
• Experience with LlamaIndex Workflow and workflow tracing
• 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)