Founding Engineer - Lead

About the role

We are looking for an experienced cloud engineer to join our founding team. Our ideal candidate is one who is passionate about software technology, constantly pushing the state of the possible, and processes a demonstrated track record of architecting, building, and scaling SaaS applications on public cloud with high concurrent usage.
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 be humble in failures; show resilience to overcome hurdles that keep you away from success. At the end of the day, your love for creating software that millions of people use and love, should make it all worth the while.

What You’ll Do:

You will lead engineering in a small startup-team building a software platform that takes away the complexity of providing amazing omnichannel customer experience (CX). You will partner with the founder to design, code, deploy, and scale a CX service that empowers businesses to engage with customers over any channel and provide rich and meaningful interactions without spending hours configuring, coding, and tuning their CX product and spending a fortune managing inefficient software.

Required Skills

Experience and mastery in all components of contemporary SaaS service

• 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 Kamilio and FreeSWITCH
• Application engines such as Node.js, Express.js
• Web technologies - Proxies, Load Balancers, CDNs, Webservers such as ELB, NGINX, Apache
• In-memory, disk-based databases, and object storage – Redis, Memcached, MySQL, AWS Bucket, 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 and debugging applications – Kibana, Grafana, Sumologic

In addition, interest and knowledge of concepts of Data Science and Machine Learning is highly desirable.

Remuneration Range

• Fixed compensation of 16 to 20 Lakhs per annum
• ESOP component of 16 to 20 Lakhs, standard vesting