AI Application Engineer

Design, develop, and integrate secure AI/GenAI solutions (LLMs, RAG, custom agents) into enterprise financial software using .NET/C# or Java microservices.

Build, scale, and maintain automated CI/CD pipelines (Azure DevOps, Jenkins, or GitHub Actions) for seamless model deployment and microservice orchestration across public cloud infrastructure (AWS/Azure/Google Cloud Platform).

Collaborate with data engineering and quantitative teams to deploy low-latency, real-time AI models for critical financial use cases like fraud detection, risk scoring, and automated compliance.

Implement robust infrastructure-as-code (Terraform/Kubernetes/Docker) alongside cloud-native security controls to ensure high availability, data privacy, and strict regulatory compliance.

Establish operational monitoring, tracking latency, token costs, and model performance/drift to maintain high-precision, production-grade AI systems in dynamic financial environments.