Staff Software Engineer - GenAI

Shape the future of trust in the age of AI
At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place.

Why join us:

• Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.

• Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.

• Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.

Job Description

Oscilar is seeking a highly experienced Staff Software Engineer - Generative AI 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

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

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

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

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

• 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 and ensure high availability.

Requirements

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

• 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).

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

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

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

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

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

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

Benefits

• Compensation: Competitive salary and equity packages, including a 401k

• Flexibility: Remote-first culture — work from anywhere

• Health: 100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US and Canada)

• Balance: Unlimited PTO policy

• Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product

• Culture: Family-Friendly environment; Regular team events and offsites

• Development: Unparalleled learning and professional development opportunities

• Gear: Home office setup assistance

• Impact: Making the internet safer by protecting online transactions

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