Senior/Staff Generative AI Engineer, Backend

Location

Remote

Background

Oscilar is seeking a highly experienced Senior Generative AI Engineer to join our backend team. In this role, you will design, build, and maintain AI-powered services that form the core infrastructure of our SaaS platform. You will work closely with cross-functional teams, integrating cutting-edge generative AI models into scalable, low-latency backend systems that cater to our global enterprise clients. Your contributions will directly impact the performance, reliability, and innovation of our platform.

Responsibilities

1. Design and implement scalable backend services that leverage generative AI models to deliver high-performance, low-latency solutions.

2. Collaborate with product, frontend, and QA teams to define technical requirements and ensure seamless integration of AI models with other platform components.

3. Optimize AI models and backend services for maximum performance, scalability, and maintainability in a distributed environment.

4. Identify and resolve bottlenecks related to AI processing and system performance, ensuring efficient resource utilization and system stability.

5. Implement best practices for deploying, monitoring, and maintaining AI models in production, including CI/CD pipelines and model versioning.

6. Proactively monitor the health and performance of AI-driven backend services, applying strategies to mitigate potential issues and ensure high availability.

Requirements

1. Bachelor’s or master’s degree in computer science, Software Engineering, or a related field.

2. 7+ years of backend software development experience, with 3+ years focusing on AI/ML, including hands-on experience with generative AI models (e.g., GPT, LLMs).

3. Strong expertise in Java and AWS technologies, with deep knowledge of building and operating low-latency, high-scale services in distributed environments.

4. Proven experience deploying and optimizing AI/ML models in production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP).

5. Familiarity with microservices architecture, RESTful APIs, and security best practices in AI services.

6. Experience with distributed data systems such as Kafka, ClickHouse, or similar technologies to manage large-scale AI workloads.

7. Strong understanding of CI/CD tools (e.g., Jenkins, Git, Maven, Gradle) and agile development methodologies, with a focus on automating model deployment.

8. Excellent problem-solving abilities, with a focus on AI model performance optimization, scalability, and system architecture.

Apply now →

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