Build our agentic services platform from zero to one. Own backend architecture from initial concept through production deployment to enterprise scale.

Responsibilities

- Architect and build core backend infrastructure using Python and FastAPI

- Design and optimize PostgreSQL databases for production workloads at scale

- Build complex workflow orchestration systems for agentic services and automation

- Implement caching strategies with Redis for high-performance data access

- Build monitoring, logging, and alerting systems with tools like Prometheus and Grafana

- Create and maintain CI/CD pipelines for rapid, reliable deployments

- Containerize services with Docker and orchestrate with Kubernetes

- Work independently with minimal direction in an ambiguous, fast-paced environment

- Establish engineering standards, security practices, and technical culture

- Own systems end-to-end from design through deployment, scaling, and incident response

Requirements

- 7+ years building production backend systems from concept to scaled deployment

- Expert-level Python with significant FastAPI experience in production

- Deep PostgreSQL proficiency: complex queries, optimization, schema design, performance tuning

- Production experience with Redis for caching, session management, and real-time data

- Hands-on experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)





- Proven track record implementing CI/CD pipelines and deployment automation

- Experience with monitoring/observability tools and maintaining system reliability

- Thrives with autonomy, minimal direction, and ambiguous early-stage problems

- Robust system design, security, and operational excellence instincts

Nice To Have

- Backend infrastructure for AI/ML applications or agentic systems

- Experience building workflow products or workflow orchestration platforms

- Managing headless browsers (Playwright, Puppeteer) at scale in production

- Experience with Neo4j or other graph databases for complex relationship modeling

- Track record scaling systems from hundreds to millions of requests

- Previous startup experience shipping rapidly and iterating based on feedback

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

📌 Founding Engineer, Backend (Senior) (Hyderabad)
🏢 Cenna
📍 Hyderabad