We are seeking an experienced Software Architect to lead the technical vision and architectural strategy of our cloud-native SaaS platform. Our team develops an Azure-based platform for building AI agents and integrating them with telephony and voice communication systems, enabling intelligent, real-time customer interactions at scale.
Our platform is built on a large-scale, distributed microservices architecture powered primarily by Node.js and deployed on Kubernetes. The technology stack includes Docker, Terraform, Azure cloud services, and advanced AI technologies such as Large Language Models (LLMs), Text-to-Speech (TTS), and Speech-to-Text (STT) services.
The ideal candidate combines deep software architecture expertise with strong hands-on engineering capabilities. They bring a proven background in cloud-native platforms, distributed systems, modern DevOps practices, and AI-driven application development. Comfortable operating across architecture, infrastructure, and implementation layers, they thrive on solving complex technical challenges.
Responsibilities:
Define and evolve the overall system architecture and technical roadmap.
Drive architectural decisions that ensure scalability, reliability, security, and performance.
Establish engineering standards, best practices, and design principles across development teams.
Provide technical leadership and mentorship to engineering teams throughout the software development lifecycle.
Collaborate closely with product, engineering, and operations teams to deliver high-quality solutions.
Participate hands-on in architecture reviews, system design, code reviews, troubleshooting, and performance optimization.
Lead cloud-native and DevOps initiatives, ensuring efficient deployment, monitoring, and operational excellence.
Promote and leverage AI-assisted development tools and practices to improve engineering productivity, code quality, and delivery velocity.
Our platform is built on a large-scale, distributed microservices architecture powered primarily by Node.js and deployed on Kubernetes. The technology stack includes Docker, Terraform, Azure cloud services, and advanced AI technologies such as Large Language Models (LLMs), Text-to-Speech (TTS), and Speech-to-Text (STT) services.
The ideal candidate combines deep software architecture expertise with strong hands-on engineering capabilities. They bring a proven background in cloud-native platforms, distributed systems, modern DevOps practices, and AI-driven application development. Comfortable operating across architecture, infrastructure, and implementation layers, they thrive on solving complex technical challenges.
Responsibilities:
Define and evolve the overall system architecture and technical roadmap.
Drive architectural decisions that ensure scalability, reliability, security, and performance.
Establish engineering standards, best practices, and design principles across development teams.
Provide technical leadership and mentorship to engineering teams throughout the software development lifecycle.
Collaborate closely with product, engineering, and operations teams to deliver high-quality solutions.
Participate hands-on in architecture reviews, system design, code reviews, troubleshooting, and performance optimization.
Lead cloud-native and DevOps initiatives, ensuring efficient deployment, monitoring, and operational excellence.
Promote and leverage AI-assisted development tools and practices to improve engineering productivity, code quality, and delivery velocity.
Requirements:
8+ years of software engineering experience, including architecture of large-scale distributed systems.
Proven experience architecting production microservices systems.
Deep understanding of cloud-native and containerized architectures.
Hands-on Kubernetes experience, including scaling, resilience, networking, and operations.
Experience using AI development tools and agents for design, implementation, troubleshooting, and architecture decisions.
Strong DevOps background with extensive hands-on experience in Infrastructure as Code, particularly Terraform.
Experience designing and governing CI/CD pipelines and deployment strategies.
Strong understanding of networking concepts including DNS, TLS, routing, NAT, proxies, load balancing, and service-to-service communication.
Experience designing secure systems and applying cloud security best practices.
Experience with Azure services and cloud architecture patterns.
Strong backend development experience with Node.js, NestJS, or similar technologies.
Strong experience with MongoDB, including schema design, scalability, performance optimization, and operational considerations.
Ability to evaluate and incorporate AI-assisted engineering practices into the software development lifecycle.
Experience with observability, monitoring, logging, tracing, and incident response.
Excellent communication skills and ability to influence technical direction across teams.
Preferred Qualifications:
Experience with real-time communication, SIP, VoIP, WebRTC, or telecom technologies.
Experience architecting SaaS platforms.
Experience leading cross-team architecture initiatives.
Familiarity with platform engineering and internal developer platforms.
Experience with AI-powered applications, AI agents, or conversational AI platforms.
8+ years of software engineering experience, including architecture of large-scale distributed systems.
Proven experience architecting production microservices systems.
Deep understanding of cloud-native and containerized architectures.
Hands-on Kubernetes experience, including scaling, resilience, networking, and operations.
Experience using AI development tools and agents for design, implementation, troubleshooting, and architecture decisions.
Strong DevOps background with extensive hands-on experience in Infrastructure as Code, particularly Terraform.
Experience designing and governing CI/CD pipelines and deployment strategies.
Strong understanding of networking concepts including DNS, TLS, routing, NAT, proxies, load balancing, and service-to-service communication.
Experience designing secure systems and applying cloud security best practices.
Experience with Azure services and cloud architecture patterns.
Strong backend development experience with Node.js, NestJS, or similar technologies.
Strong experience with MongoDB, including schema design, scalability, performance optimization, and operational considerations.
Ability to evaluate and incorporate AI-assisted engineering practices into the software development lifecycle.
Experience with observability, monitoring, logging, tracing, and incident response.
Excellent communication skills and ability to influence technical direction across teams.
Preferred Qualifications:
Experience with real-time communication, SIP, VoIP, WebRTC, or telecom technologies.
Experience architecting SaaS platforms.
Experience leading cross-team architecture initiatives.
Familiarity with platform engineering and internal developer platforms.
Experience with AI-powered applications, AI agents, or conversational AI platforms.
This position is open to all candidates.
