Software Engineer - Python & Cloud (Backend)
IT - Software / DB / QA / Web / Graphics / GIS
About the Employer
Job Description
Software Engineer – Python & Cloud (Backend)
Full-Time | Python / FastAPI | Cloud Platform
ABOUT THE ROLE
We are building a multi-tenant fraud detection API that scores users in real time using email, phone, and IP signals from multiple third-party vendors. The platform is in its pilot phase, built with Python/FastAPI, PostgreSQL, Redis, and scikit-learn, deployed on a cloud platform. We are looking for an engineer who can operate across the full stack: API development, vendor integrations, deployment, and ML model decision logic.
KEY RESPONSIBILITIES
API & Backend
- Build and maintain FastAPI endpoints with multi-tenant authentication, rate limiting, and structured audit logging
- Own the Redis caching layer, circuit breakers for vendor resilience, and session management across application instances
- Write and manage Alembic database migrations against PostgreSQL
Infrastructure & DevOps
- Provision and maintain cloud infrastructure (compute, managed Postgres, Redis, object storage, load balancing)
- Maintain CI/CD pipelines via GitHub Actions including Docker builds, Trivy security scans, and rolling deployments
- Monitor system health via Prometheus metrics and alerting; respond to on-call incidents
ML & Decision Framework
- Maintain and evolve the fraud scoring decision framework — thresholds, model overrides, and per-tenant policy configs
- Support scikit-learn model versioning, audit hash tracking, and deterministic replay of past decisions
- Contribute to feature engineering and signal design as new vendor data sources are integrated
QUALIFICATIONS
- 3+ years of backend engineering experience with Python in a production environment
- Solid understanding of REST API design, async Python (FastAPI or similar), and relational databases (PostgreSQL)
- Hands-on experience with Docker and deploying to any cloud platform ( AWS, GCP, or Azure)
- Comfortable with CI/CD pipelines (GitHub Actions or equivalent) and container security practices
- Comfortable with automated testing and a code-review / CI-gated workflow
- Familiarity with ML concepts — model inference, feature pipelines, decision thresholds — even without deep data science background
- Experience with Redis or similar caching/messaging systems
NICE TO HAVE
- Exposure to container orchestration or infrastructure-as-code
- Knowledge of fraud detection, KYC/AML, or fintech compliance
- Familiarity with scikit-learn model training, MLflow
- Experience with observability tooling like Prometheus, Grafana, or similar
HOW TO APPLY
If you meet the above prerequisites, please forward your application to:
