Software Architect

We are on a mission to unlock impossible AI for all.

Imagine a world in which breakthrough discoveries are commonplace. Here at RAIC Labs, we help organizations transcend data-access and data-quality issues, unleashing the full impact of AI in all fields. Simply put, our technology unlocks previously impossible AI that has the power to change the world.

That’s all well and good, but despite our high-tech profile, we recognize that none of this is possible without our people. Which is why we’re thrilled to be adding a Software Architect to our RAIC Edge team. In this role, you’ll be responsible for the full software development lifecycle, from conception to deployment. Ideally, you’ll be comfortable with both front-end and back-end coding languages, development frameworks, and third-party libraries.

Here’s what you’ll be working on:

• Provide technical leadership and vision for the design and development of our RAIC Edge product platform utilizing modern Computer Vision & AI techniques.
• Drive initiatives to improve system reliability, availability, and performance, applying best practices in areas such as fault tolerance, monitoring, and automation
• Building cutting edge user interfaces – bridging human interaction with AI
• Collaborating with the AI team to optimize results and performance
• Working with product management team to ideate new features
• Identifying tech debt and contributing to code refactoring
• Troubleshooting high priority customer facing bugs
• Interacting with QA team to ensure software quality on regular product releases

Are you up for the challenge? Read on to see if this will be the right fit for you! 

A good Software Architect at RAIC Labs must have the following skills, knowledge, education and experience:

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering or Management Information Systems
• 8+ years of software architect experience
• Hold a security clearance
• C# / .NET / Python
• NET / Fast API / DAPR
• Modern front-end frameworks (such as ReactJS)
• Deploying, maintaining, and troubleshooting local Docker environments
• Microservice implementation and design
• Unit Testing & SOLID principles

If you want to go above and beyond, bring these skills and characteristics to the table:

• Training Computer Vision AI models and preparing data pipelines
• Understanding of GPU-accelerated compute environments
• Managing air-gapped Edge application environments
• Docker compose / K3S or similar distributions
• Distributed Application Runtime (DAPR)
• Edge based Identity Providers (such as Authentik / Keycloak)
• Redis Cache
• Modern CI/CD platforms and workflows

AI is a complex field with a lot of processes and technologies to learn, and here at RAIC Labs, the sky’s the limit! If you’re a Software Architect looking for greener pastures, we should talk.