Senior Python Engineer - AI Systems

Remote Full-time
This is a remote position.
Our client, an AI-focused startup based in Toronto, Canada, is building AI-powered financial report generation software for enterprise clients. The platform leverages Python and large language models (LLMs) to generate complex, high-quality reports at scale.

They are currently seeking a Senior Python / AI Engineer to take ownership of production reliability and system performance across their core platform. This is not a feature-delivery role - it is a systems ownership role for engineers who understand what it takes to build, operate, and maintain production-grade AI systems.

Location: India (Remote, must be able to work in IST/EST hours)
Employment Type: Full-Time
Experience: 4-6+ years
Tech Stack: Python, FastAPI, LLM

What You'll Do

Own end-to-end production systems: design, build, deploy, monitor, and continuously improve.

Build and maintain Python-based backend services (FastAPI preferred) powering AI workflows.

Develop and optimize LLM pipelines (RAG, prompt workflows, data processing) in production environments.

Lead incident response, debugging, and root cause analysis for production issues.

Improve system reliability, testing practices, and release quality.

Work closely with Product to translate requirements into scalable technical solutions.

Implement and maintain observability, logging, and monitoring systems.

Contribute to architecture decisions with a focus on performance and scalability.




Requirements
What You Bring

Python-first engineer (FastAPI or similar frameworks preferred).

Proven experience building AND maintaining systems in production - not just developing features.

Hands-on experience with LLMs in production environments (not just API integrations or prototypes).

Strong experience with production debugging, incident response, and system reliability.

Background working at a product company (startup or product-driven environment preferred).

Solid understanding of backend architecture, APIs, and data pipelines.

Experience with cloud infrastructure (GCP preferred), Docker, and CI/CD.

Strong ownership mindset - takes responsibility for systems end-to-end.

Experience with financial data, reporting systems, or data-heavy applications.

Familiarity with RAG pipelines, LangChain, or similar frameworks.

Experience scaling systems handling large datasets or high-volume workloads.


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