Backend & DevOps Engineer – AI/LLM

About BlackEdge BlackEdge is a growing publicly traded financial group operating across mortgages, payments, and corporate financing, providing credit and financing solutions to consumers and businesses. We combine financial expertise, an entrepreneurial mindset, and technology to develop advanced financial solutions and create meaningful value for our customers. About the role We’re looking for a Backend & DevOps Engineer to join our Technology team and build and operate enterprise AI systems in production. The role combines backend development for AI and LLM applications with the implementation, maintenance, and operation of cloud and DevOps infrastructure in broadly comparable scope. The emphasis between these areas may evolve depending on the stage of each project and the needs of the team. You will take ownership across the entire system lifecycle—from design and development through infrastructure, deployment, monitoring, troubleshooting, and production optimization. This is a hands-on role for an engineer who enjoys working across the technology stack, taking end-to-end ownership, and connecting application code, cloud infrastructure, and AI capabilities. What you’ll be doing DevOps and cloud infrastructure · Building and maintaining cloud infrastructure using Terraform, including environments, networking, storage, and access management. · Developing and maintaining CI/CD pipelines for automated testing, Docker image builds, deployments, and rollbacks. · Implementing monitoring, logging, and alerting, troubleshooting production issues, and improving system reliability, performance, and cost efficiency. · Managing secrets, identities, and permissions while ensuring secure communication between services. Backend and LLM applications · Developing backend services using Python and FastAPI, including REST APIs, asynchronous workflows, queues, and background jobs. · Integrating language models into applications using tool calling, structured outputs, streaming, and conversation-context management. · Building document-processing, knowledge-retrieval, and RAG workflows that connect language models with enterprise information. · Developing integrations with internal enterprise systems and external services. · Writing automated tests and evaluating AI workflows for quality, reliability, latency, and token usage. What you’ll need · At least 3 years of hands-on experience developing Python backend services and operating them in production. · Practical experience with at least one major cloud provider: Azure, AWS, or GCP. · Hands-on experience with Terraform, Docker, Linux, and CI/CD pipelines. · Experience with REST APIs, asynchronous programming, relational databases such as PostgreSQL, and message queues. · Practical experience building LLM applications and integrating model APIs. · A solid understanding of authentication, authorization, secrets management, and service security. · The ability to work independently, navigate existing codebases, and troubleshoot issues across application and infrastructure layers. · A strong sense of ownership, the ability to write clear and maintainable code, and a collaborative approach to development. Nice to have · Approximately five years of relevant experience in backend, DevOps, or a similar hybrid engineering role. · Hands-on Azure experience, particularly with Container Apps, Key Vault, Microsoft Entra ID, and Service Bus. · Experience developing AI agents and working with tool calling and the Model Context Protocol (MCP). · Experience with RAG, embeddings, vector search, and pgvector. · Familiarity with OpenTelemetry, Grafana, and distributed-system monitoring. · Experience integrating with Microsoft Graph and Microsoft 365. Ready to build and operate AI systems that bring together backend engineering, cloud infrastructure, and advanced LLM capabilities? We’d love to meet you. This is a full-time, office-based position at our Tel Aviv office. The position is open to candidates of all genders. Please send your CV to careers@blackedge.co.il . Show more Show less