Principal Backend Architect

We are looking for a Principal Backend Architect to lead the design, architecture, and scaling of Revspot's backend systems. This role is meant for someone who can think deeply about system design, scalability, performance, reliability, and long-term engineering decisions. You will work closely with the CTO, engineering leaders, product, data, and AI teams to build backend systems that power Revspot's AI-native revenue infrastructure. The ideal candidate should be hands-on, technically strong, and comfortable owning complex architecture decisions from design to execution.
The core responsibilities for the job include the following:
Own backend architecture and system design:
Design scalable, reliable, and secure backend systems.
Define architecture patterns, service boundaries, APIs, and data flows.
Ensure the backend can support high-volume, real-time, and AI-driven workflows.
Build and scale core backend platforms:
Work on backend services that power AI agents, lead qualification, calling workflows, automation, CRM integrations, analytics, and customer-facing systems.
Improve system performance, reliability, observability, and fault tolerance.
Drive technical decision-making:
Evaluate and select the right technologies, frameworks, databases, infrastructure, and design patterns.
Create clear technical design documents, architecture reviews, and implementation plans.
Help the team make trade-offs between speed, scalability, and maintainability.
Mentor and guide engineering teams:
Guide senior and mid-level engineers on system design, backend best practices, and code quality.
Review critical technical designs and major pull requests.
Raise the overall engineering maturity of the backend team.
Improve engineering standards:
Set standards for API design, database design, performance, testing, monitoring, logging, deployment, and security.
Build processes that reduce production issues and improve engineering velocity.
Work closely with product and business teams:
Translate business requirements into scalable technical solutions.
Partner with product and AI teams to build systems that support fast experimentation without breaking reliability.
Own reliability and performance:
Identify system bottlenecks and improve latency, throughput, uptime, and cost efficiency.
Drive improvements in monitoring, alerting, debugging, incident management, and post-mortems.
Requirements:
8+ years of experience in backend engineering, distributed systems, or platform engineering.
Strong experience designing and scaling backend systems in high-growth environments.
Strong proficiency in Python / Java / Node.js / Go or similar backend languages.
Deep understanding of system design, microservices, APIs, queues, event-driven architecture, and distributed systems.
Strong database experience with MySQL / PostgreSQL and NoSQL databases such as MongoDB / Redis / DynamoDB.
Experience with cloud infrastructure, preferably AWS.
Strong understanding of performance optimization, caching, indexing, async processing, and system reliability.
Experience with observability tools, logging, monitoring, alerting, and incident management.
Ability to write clean, maintainable, and production-grade code.
Strong communication skills and ability to explain complex technical decisions clearly.
Prior experience mentoring engineers and leading architecture discussions.
Good to Have:
Experience building LLM-based applications, AI agents, voice agents, or automation platforms.
Experience with real-time systems, call systems, CRM integrations, workflow engines, or sales/marketing automation.
Experience working in fast-paced startups.
Experience with Kubernetes, Docker, CI/CD, Terraform, or infrastructure-as-code.
Experience with security, compliance, and data privacy best practices.

Experience
7-11 yrs