Chief Technology Officer - Proofline

About the role

Proofline is live in production with institutional pilots underway. The Pod Lead owns the backend platform end-to-end, including the scale-up and the platform strategy across our planned free, premium, and enterprise tiers and leads the four-engineer Bengaluru team, reporting to the founder.

Responsibilities

• Own production reliability, deployment, and observability for a Python microservices platform on GCP; maintain a daily-release cadence.
• Own the tier strategy end-to-end and build the monetization layer: metering, tier enforcement, billing integration, entitlements.
• Drive enterprise readiness: SSO and tenancy hardening, audit logging, SOC 2 preparation.
• Set and enforce engineering standards; review all backend work, including AI-agent-generated code.
• Manage and mentor the pod; own delivery against the product roadmap with the founder; help design the hiring of the remaining seats.

Requirements

• You treat AI IDEs as a force multiplier, but you own the architecture, quality, and production-readiness that AI can't.
• Backend/platform depth including years owning production systems at a product company; zero-to-one or founding-engineer experience strongly preferred.
• Expert Python (FastAPI/Django/Flask) and strong cloud depth (GCP or AWS): containers, CI/CD, IaC, monitoring.
• Experience with billing, metering, or entitlement systems at scale.
• AI-native working style: daily use of coding agents (Claude Code, Codex-class tools) with a clear point of view on reviewing AI-generated code.
• Prior team-lead or tech-lead experience.

Nice to Have

• Experience running multi-tenant and single-tenant / on-prem-style fleets with per-customer isolation, upgrade paths, and migration compatibility.
• Already orchestrate AI coding agents in your workflow and have opinions about where they break.

How We Work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation—your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

You Should Apply If

• You enjoy turning messy problems into concrete solutions.
• You thrive in fast-moving, low-process environments.
• You're excited about production engineering (monitoring, reliability, cost, latency).

You Should Not Apply If

• You want remote/hybrid (this is onsite Bangalore only).
• You prefer narrow tickets and minimal ambiguity.
• You prefer highly structured, slow-moving product organizations.

The Recruiter for this role is Ritesh Kalvellu. Apply to the role directly, and he will get back to you if your profile is relevant to the hiring requirements.