Senior Software Engineer, Iru AI

Iru•Miami, FL

12d•Hybrid

About The Position

As a Senior Software Engineer, you will play an important role in designing and building the services that power IruAI. You will collaborate closely with engineers, product managers, and designers to deliver reliable, scalable, and secure software systems. In this role, you will contribute to the development of modern backend architectures while helping integrate AI-powered capabilities into our platform. You will work with Large Language Models (LLMs) and AI tooling to help build intelligent product features and internal development tools. You will be expected to take ownership of key components, contribute to system design discussions, and help drive engineering best practices across the team. Required to work on-site in our Coral Gables office Tuesday â Thursday.

Requirements

3â6 years of professional software engineering experience
Strong proficiency in backend programming languages such as Python, Go, or Java
Experience designing and building RESTful APIs and/or gRPC services
Familiarity with service-oriented architecture and microservices patterns
Experience working with cloud platforms such as AWS or GCP
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 SQL and relational databases such as Postgres or MySQL
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
Experience participating in peer code reviews and collaborative engineering processes

Nice To Haves

Experience with Python-based AI/LLM application development
Experience integrating Large Language Models (LLMs) into backend systems
Familiarity working with AI model APIs such as: Anthropic Claude OpenAI models
Experience using Pydantic or similar schema validation frameworks for structured AI responses and API validation
Familiarity with prompt engineering, AI tool orchestration, or agent-based systems
Experience building systems that support AI inference pipelines or AI-driven product features
Exposure to frontend technologies such as React
Familiarity with CDNs and caching strategies
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
Experience building AI agents or tool-driven LLM systems
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

Responsibilities

Build and Maintain Backend Services: Design, develop, and maintain reliable backend services and APIs that support core product functionality.
Contribute to System Architecture: Work with senior engineers to design scalable service architectures and implement distributed systems that are resilient and maintainable.
Develop AI-Powered Features: Contribute to the implementation of AI-driven capabilities using modern LLM platforms and APIs to enhance product functionality and developer productivity.
Improve Developer Workflows: Collaborate with platform and infrastructure teams to improve local development environments, CI/CD pipelines, and testing workflows.
Build Scalable Systems: Develop systems designed to scale as the product and customer base grow while maintaining reliability and performance.
Implement Messaging and Integration Patterns: Help build and maintain event-driven services and integrations using message brokers such as Kafka or similar technologies.
Collaborate Across Teams: Work closely with product managers, designers, and other engineers to translate product ideas into technical solutions.
Write High-Quality Code: Maintain strong coding standards through testing, code reviews, and adherence to engineering best practices.
Continuously Improve the Platform: Identify opportunities to improve performance, reduce technical debt, and strengthen system reliability.