Senior AI Software Engineer

We are seeking a highly motivated Software Engineer to join our growing AI/ML team. The ideal candidate combines strong software engineering fundamentals with hands-on experience developing AI-powered applications and services.

In this role, you will build scalable backend systems, APIs, and cloud-native solutions while contributing to Generative AI initiatives, including LLM-based applications, Retrieval-Augmented Generation (RAG) pipelines, and Agentic AI systems. You will leverage modern AI-assisted development tools to accelerate delivery while maintaining high standards for code quality, testing, security, and maintainability.

This position is ideal for engineers who enjoy solving complex technical challenges, rapidly prototyping innovative solutions, and delivering production-ready software in a collaborative, fast-paced environment.

Software Engineer with strong backend development expertise and experience building AI-enabled applications using Large Language Models, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks within cloud-native environments.

• Design, develop, test, and deploy scalable backend services and APIs, primarily using Python.
• Build modular, maintainable, and well-tested software following engineering best practices and clean architecture principles.
• Utilize AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, or similar solutions to improve development productivity while maintaining code quality and accountability.
• Rapidly prototype and iterate on new features while balancing speed, maintainability, and long-term scalability.
• Develop and integrate LLM-powered capabilities, including prompt engineering workflows and Retrieval-Augmented Generation (RAG) solutions.
• Design and implement agentic and multi-agent systems capable of task orchestration, reasoning, and tool utilization.
• Containerize applications using Docker and deploy scalable workloads through Kubernetes.
• Build and maintain CI/CD pipelines to automate testing, integration, deployment, and release management.
• Deploy and manage applications across cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Collaborate with data scientists, product managers, architects, and software engineers to translate business requirements into production-ready solutions.
• Optimize application performance, latency, scalability, and operational costs, including AI-driven services.
• Implement security, monitoring, logging, and observability best practices across software platforms.
• Stay current with emerging software engineering practices, AI technologies, cloud-native architectures, and developer productivity tools.
• Design, develop, test, and deploy scalable backend services and APIs, primarily using Python.
• Build modular, maintainable, and well-tested software following engineering best practices and clean architecture principles.
• Utilize AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, or similar solutions to improve development productivity while maintaining code quality and accountability.
• Rapidly prototype and iterate on new features while balancing speed, maintainability, and long-term scalability.
• Develop and integrate LLM-powered capabilities, including prompt engineering workflows and Retrieval-Augmented Generation (RAG) solutions.
• Design and implement agentic and multi-agent systems capable of task orchestration, reasoning, and tool utilization.
• Containerize applications using Docker and deploy scalable workloads through Kubernetes.
• Build and maintain CI/CD pipelines to automate testing, integration, deployment, and release management.
• Deploy and manage applications across cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Collaborate with data scientists, product managers, architects, and software engineers to translate business requirements into production-ready solutions.
• Optimize application performance, latency, scalability, and operational costs, including AI-driven services.
• Implement security, monitoring, logging, and observability best practices across software platforms.
• Stay current with emerging software engineering practices, AI technologies, cloud-native architectures, and developer productivity tools.