This is a remote position.

Are you an expert in Python and have built scalable software solutions? Do you know how to handle heavy volumes of data and process the responses as APIs? Are you looking to work on cool AI project?

Join the Arya.ai – fast growing ‘AI’ startup, with team of researchers and experts to democratize ‘deep learning’.

Why Us:

Arya.ai solves niche problems in the financial services industry. And many times, which are underserved and unsolved. This means, you not only get to work with leading FIs but also be the first to solve the problem in the industry. We are a people first organization with a very open culture.

Arya.ai’s team consists of highly experienced researchers and data scientists in deep learning and machine learning. Since 2013, Arya.ai has worked with leading enterprises like banks, insurance companies and financial service players across the globe.

We are looking for Sr Software Engineers who -

• Expert in Python and have built scalable systems.
• Has experience with Puppet/Chef/Ansible, Amazon Web Services (AWS), Git, Graphite and related tools for large-scale systems management is a must.
• Should be able to write python, bash, c/c++ and perl scripts.
• Good understanding of architecture and tradeoffs in distributed computing environments.
• Experience working with linux system monitoring and analysis.
• Should be hands on Cloud like aws ec, elb, s3 bucket, auto scale etc.
• Better understanding of nginx/Apache web server as reverse proxy , load balancer, caching. H/w, S/w load balancer.
• Experience with web infrastructure, distributed systems, or component-oriented software engineering

Requirements

What you'll be doing:

• Design and implementation of the network that supports for easy deployments of the servers
• Building exciting new features that will enable developers to build highly available, robust AI services
• Maintaining and ensuring a high standard for reliability and availability across multiple datacenters
• Evolving our existing architecture and codebases to support building flexible networking capabilities both internally and for the product