About the job
Join Us in Shaping the Future of AI-Driven Trust
At Oscilar, we are at the forefront of developing the most sophisticated AI Risk Decisioning™ Platform. Trusted by banks, fintech companies, and digitally engaged organizations, we harness the power of artificial intelligence to help manage fraud, credit, and compliance risks. If you are dedicated to tackling complex challenges and enhancing internet safety, this is the place for you.
Why You Should Consider Joining Us:
Mission-Driven Culture: Collaborate with seasoned professionals from leading companies like Meta, Uber, Citi, and Confluent, all working towards a common aim of making the digital landscape safer.
Empowerment and Impact: We advocate for extreme ownership. You will be encouraged to take initiative, act swiftly, and make impactful decisions that advance our mission.
Innovate at the Forefront: Your contributions will play a crucial role in transforming how modern finance detects fraud and manages risk.
Job Overview
Oscilar is on the lookout for a highly skilled Staff Software Engineer specializing in Generative AI to enhance our backend team. In this pivotal role, you will design, develop, and maintain AI-driven services that are integral to our SaaS platform's infrastructure. Collaborating closely with cross-functional teams, you will integrate state-of-the-art generative AI models into scalable, low-latency backend systems tailored for our global enterprise clients. Your work will significantly influence the performance, reliability, and innovation of our platform.
Key Responsibilities
Design and implement scalable backend services utilizing generative AI models to deliver high-performance, low-latency solutions.
Work collaboratively with product, frontend, and QA teams to define technical requirements and ensure smooth integration of AI models within the platform.
Optimize AI models and backend services for superior performance, scalability, and maintainability within a distributed environment.
Identify and troubleshoot performance bottlenecks associated with AI processing and system stability, ensuring efficient resource use.
Implement best practices for deploying, monitoring, and maintaining AI models in production, including CI/CD pipelines and model versioning.
Proactively monitor the health and performance of AI-driven backend services, applying strategies to mitigate potential issues.
