Haris Zafar

Senior Software Architect with 12+ years of experience building scalable SaaS platforms, cloud-native systems, and AI-driven automation frameworks. Specialized in autonomous CI/CD pipelines, AI agent orchestration, multi-tenant architecture, and cost-optimized cloud infrastructure. Strong background in TypeScript, Node.js, Python, PostgreSQL, and distributed systems design. Focused on reliability engineering, observability, and developer velocity at scale.

Senior Software Architect (Present)

• Architected multi-tenant SaaS platforms serving high-growth user bases with strict data isolation policies.
• Designed autonomous CI/CD systems enabling staged deployment, canary release strategies, and automated rollback based on real-time error thresholds.
• Built AI-assisted development pipelines where agents generate PRs, run validation loops, and deploy small-to-medium changes autonomously.
• Implemented blast radius control systems differentiating UI-only changes from API, database, authentication, and billing modifications.
• Optimized cloud infrastructure costs by auditing resource usage, reducing unnecessary compute, and improving database performance.
• Designed background job architectures using Redis and queue workers with retry logic, batching, and failure monitoring.
• Integrated observability layers tracking deployment frequency, MTTR, agent success rates, and system health metrics.
• Led engineering teams, conducted architecture reviews, and implemented coding standards for maintainability.

Cloud & Infrastructure Leadership (Present)

• Managed production workloads across GCP and AWS environments.
• Optimized Cloud Run and serverless workloads for concurrency and cost efficiency.
• Designed high-availability database systems with indexing and query optimization strategies.
• Built monitoring and alerting systems for proactive issue detection and rapid incident response.
• Established structured environment separation across development, staging, and production.

AI Systems & Autonomous Development (Present)

• Developed agent orchestration layers that classify tasks by complexity and risk before dispatching execution.
• Implemented T-shirt sizing automation based on code diff size, dependency impact, and test coverage analysis.
• Integrated model routing systems selecting appropriate LLMs based on task type, context window, and cost constraints.
• Designed structured system prompts for operational AI, enabling deterministic execution rather than creative output.
• Built self-healing pipelines with circuit breakers and escalation thresholds for complex incidents.
• Instrumented agent loops with telemetry, evaluation checks, and logging for observability and governance.