Backend/Devops Engineer

What We Are Looking For

The Intelecy platform is super-simple:

1. Fetch data from customers
2. Analyze data
3. Push real-time analytics back to the customer
4. Provide tools for real-time and historical analytics

We are looking for engineers to works on parts 1-4. We are closing in on one billion data points (sensor readings, production information, etc.) per day, so everything we do needs to scale.

What might you work on?

Easy stuff:

• Extend our APIs with new management and data analysis interfaces
  • Query a remote agent and list all new available sensors
  • Select two sensors and return historical data aggregated (time-weighted) for display in a scatter plot

Hard stuff:

• Build an API and backend support for orchestrating hundreds (or thousands) of customer-specific inference models fed by real-time data streams
• Design and implement a service for on-demand, compute-intensive data analytics without blowing the cloud budget

Must Have

• Significant C# experience — you’ll spend most days with dotnet, hope you like it
• Experience with HTTP API design and implementation — good API design is key to product velocity
• At least one of: Azure, GCP or AWS — Racking servers is so 2000 and late
• Git and PR-based workflows — feature branches, collaborative feedback, LGTM
• Basic SQL knowledge — behind every ORM is still SQL
• Basic Linux admin experience — IT runs on the cloud, and the cloud runs on Linux (and we use Ubuntu)
• Basic knowledge of containerized application deployments — it works on my machine; it works in my local container

Bonus Points For (or what you will learn)

• Experience with large amounts of time-series data
• Terraform experience
• GraphQL experience
• Nomad and/or Kubernetes experience
• Knowledge of serverless architecture and implementation
• Experience with Golang, Python or TypeScript
• Experience with Kafka and/or NATS
• Experience with machine learning (e.g. Tensorflow)
• Experience with Azure DevOps and pipelines

Our Tech Stack

• REST/GraphQL based API server written in C#, using Entity Framework, and hosted within Azure
• React-based frontend application using TypeScript and Tailwind CSS
• ClickHouse and SQL Server databases
• Kafka and NATS JetStream for streaming data transport and distribution
• Nomad container orchestration
• Azure DevOps for source control and CI/CD
• Hashicorp’s Terraform for managing infrastructure-as-code
• Python/Rust for most machine learning services
• Go for edge applications