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 in real time.

Youll 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 Youll 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 to 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).