Founding Engineer – Fullstack

Introduction
We are looking for ambitious cloud engineers who aspire for excellence and are looking to accelerate their professional growth by performing in the fast-paced environment of an early-stage startup. The ideal candidate is one who is passionate about software technology, constantly pushing the state of the possible, and processes a demonstrated track record of building high quality SaaS applications on public cloud at scale for at least the past three years.
Success here would need tackling the tough contradictions of working in an early-stage startup. You should be comfortable with ambiguity and constant change, yet drive clarity and focus. Love complete ownership, but collaborative in your approach in moving the team forward. You need to move fast but ensure quality. You should not be afraid of and humble in failures but processes the resilience to overcome hurdles that keep you away from success. But, at the end of the day, your love for building software that millions of people use and love, should make it all worth the while.
What You’ll Do
You will own a key component of the software platform and work with the founder to design, code, deploy, and scale the service.
Required Skills
Experience and mastery in all components of contemporary SaaS platforms more specifically
• Python and associated frameworks such as FastAPI, Pytest, Selenium, Scrapy
• Media technologies such as WebRTC, SIP/RTP, Websocket-Chat, IMAP/SMTP
• Infrastructure components for voice media such as Kamailio and FreeSWITCH
• Application engines such as Node.js, Express.js
• Knowledge of front-end technologies such as HTML, JavaScript, Angular/React, Tailwind/Bootstrap, CSS
• Web deployment technologies - Proxies, Load Balancers, CDNs, Webservers such as ELB, NGINX, Apache
• In-memory, disk-based databases, and object storage – Redis, Memcached, MySQL, S3, Glacier
• Queuing and messaging technologies – Kafka, RabbitMQ
• API Gateway and security technologies such as Zscaler
• Containerization and deployment technologies such as Docker and Kubernetes cluster management
• Managing CI/CD pipelines
• Logging, debugging, and monitoring applications – Kibana, Grafana, Sumologic, New Relic, Cloudwatch, Pagerduty
In addition, interest and knowledge of concepts of Data science and Machine learning is highly desirable.

Remuneration Range

• Fixed compensation of 9 to 11 Lakhs per annum
• ESOP component of 5 to 10 Lakhs, standard vesting