Senior Full - Stack Engineer

As a Senior Full-stack Engineer, you should be comfortable with both backend (preferably Golang) and frontend (preferably React). You will be primarily working on architecting and shipping new backend features like new integrations, enabling more machine learning APIs, building complex workflows, and various growth hacking efforts. You will also work on optimizing response times and building features that will scale to hundreds of millions of documents we process every month.

Requirements:

• Agility in shipping features.
• Good at code design and architecture.
• Great communication.
• Backend experience - preferably Golang, Python.
• Databases - understanding of data modeling for NoSQL, preferably Cassandra.
• Strong fundamentals in OOP design patterns.
• Basic understanding of DevOps.
• Curiosity and willingness to learn new things while solving a challenging problem.
• Learning and incorporating best practices in software development, security, and design/architecture.
• B. E. /B. Tech, preferably from a Tier 1 college.
• 5-8 years in software development with a strong foundation in software architecture and design, as well as one of frontend or backend development.
• Proficiency in programming and development technologies.
• Strong familiarity with DevOps best practices and tools.
• Innovative mindset and a passion for driving engineering excellence.

Some of the interesting features we have shipped in the backend:

• Compile Python code into C, which could be imported into Go and then shipped as a binary for on-premises systems.
• Autoscale GPU-dependent services with Kubernetes with a custom metric.
• Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics.
• Building a large number and variety of integrations with relatively generic interfaces like Salesforce, QuickBooks, RPAs, and external databases.
• Process a large number of files in a highly distributed manner in Golang.
• Intelligent lookups leveraging vector databases with data synced from ERP systems.

Some of the interesting things we have shipped in the frontend are the following:

• Ability for users to annotate documents so AI can learn which fields to extract.
• Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics.
• Letting users build complex visual workflows around our API in our product.
• Let users visualize complex ML metrics in a very simple and intuitive way.