Senior Software Engineer, Full Stack, Iru AI
Hybrid · Miami, Florida, United States
Job Summary
As a Senior Software Engineer at Iru AI, you will design, build, and deliver end-to-end systems that power the platform, focusing on full-stack feature development. Key responsibilities include contributing to system architecture spanning frontend, backend, and data layers, developing AI-powered features, and improving developer workflows. The role requires strong proficiency in backend languages like Python, Go, or Java, and modern frontend frameworks such as React or TypeScript, along with experience integrating AI features into user interfaces. Additionally, familiarity with services architecture, event-driven systems, and CI/CD practices is essential.
Required Qualifications
- 3–6 years of professional software engineering experience
- Strong proficiency in backend languages (Python, Go, or Java) and modern frontend frameworks (e.g., React, TypeScript)
- Experience integrating AI/LLM features into user-facing interfaces (e.g., chat UIs, copilots, automation workflows)
- Familiarity with prompt engineering, AI tool orchestration, or agent-based systems
- Experience building AI agents or tool-driven LLM systems
- Experience designing and building RESTful APIs and/or gRPC services
- Experience building and deploying full-stack applications on cloud platforms such as AWS or GCP
- Familiarity with service-oriented architecture and microservices patterns
- Experience working with event-driven architectures and message brokers (e.g., Kafka, RabbitMQ)
- Experience building and deploying services using Docker and container orchestration platforms such as Kubernetes or ECS
- Proficiency with databases and experience modeling data for both backend systems and frontend consumption
- Experience writing unit and integration tests
- Familiarity with CI/CD pipelines and modern deployment practices
- Ability to analyze problems, break them down, and deliver scalable solutions
Desired Qualifications
- Experience using Pydantic or similar schema validation frameworks for structured AI responses and API validation
- Experience building systems that support AI inference pipelines or AI-driven product features
- Experience with E2E testing frameworks such as Playwright
- Experience working with API gateways (e.g., Kong, AWS API Gateway)
- Familiarity with service meshes (e.g., Dapr, Linkerd, Istio)
- Experience implementing observability practices, including logging, metrics, and distributed tracing
- Familiarity with vector databases, embeddings, or retrieval-augmented generation (RAG)
- Experience building internal developer tools powered by AI
- Experience working in high-growth startup environments
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