Senior Python Engineer

We help creators get more out of every conversation with AI-powered chat automations for Instagram, Messenger, WhatsApp, and TikTok. The result? Better engagement, more sales, and real, sustainable growth.

With a diverse team of 400+ people spread across three continents, we’re building the leading Chat Marketing platform — with AI woven into how we build, how we work, and how we grow. Used and loved by more than 1.5 million customers worldwide.

We’re hiring a Senior Python Engineer to help build and scale backend systems that power Manychat's core product, used by millions of customers worldwide.

Depending on the product area, your work might span APIs, integrations, automation workflows, analytics, AI-powered features, or platform capabilities. What stays consistent is the scale, the ownership, and the quality of the problems.

This role is ideal for someone who enjoys building scalable backend architecture, thinking through distributed system tradeoffs, and owning work from technical design through production deployment. Reliability, performance, and observability are things you actually care about. And while you're clearly a backend person, you don't lose sight of the product or the people using it.

If you thrive in fast-moving product environments, enjoy solving ambiguous problems, and want to shape how Python services evolve at Manychat, we'd love to meet you.

We're two teams with one foundation: Python and a shared belief that engineers should own what they build, end to end. The AI Product Team ships the AI logic behind Inbound Agents, including LLM selection, integration, and production monitoring. The Data Platform Team focuses on turning enormous amounts of raw data into fast, intuitive experiences.

• →Design, build, and scale Python backend services that power high-impact product experiences used by millions of customers.
• →Work on complex backend challenges across APIs, integrations, automation workflows, data systems, AI-powered features, and platform capabilities.
• →Build async services that handle high load, latency-sensitive workflows, and real-world production traffic.
• →Design reliable service contracts and integrations between systems, including internal services and external platforms.
• →Solve architecture problems around scalability, data consistency, caching, retries, idempotency, observability, and safe failure handling.
• →Own features end to end, from technical discovery and system design to implementation, deployment, monitoring, and iteration.
• →Improve production reliability through monitoring, logging, alerting, tracing, and performance optimization.
• →Make thoughtful tradeoffs between speed, reliability, maintainability, and long-term platform evolution.
• →Contribute to CI/CD, testing strategy, rollout practices, and engineering standards for Python services.
• →Collaborate closely with Product, Design, Platform, Data, AI, SRE, and other engineering teams to turn ambiguous problems into shipped systems.
• →Help shape how Python backend engineering evolves at Manychat as we scale the product and platform.

You’ll need:

• 5+ years of commercial backend engineering experience, with strong hands-on Python expertise.
• Experience building and maintaining high-load production systems.
• Strong knowledge of async programming, concurrency, and modern Python frameworks such as FastAPI.
• Experience designing, building, and integrating REST APIs.
• Solid knowledge of relational databases and SQL, preferably PostgreSQL.
• Strong testing practices, including unit and integration testing.
• Experience with CI/CD, production deployments, monitoring, and Docker or similar tooling.
• Good understanding of system design, reliability, scalability, and maintainability.
• Strong ownership, autonomy, and ability to work through ambiguity.
• Product mindset and experience collaborating with cross-functional teams.

It would be great if you have:

• Experience with Redis, queues, caching, or event-driven systems.
• Experience with distributed systems and service-to-service communication.
• Familiarity with observability tools such as Grafana, Prometheus, or OpenTelemetry.
• Experience with cloud infrastructure or Kubernetes.
• Exposure to AI/ML-powered products, data platforms, analytics systems, or large-scale third-party integrations.