Senior Python Engineer

We are looking for a strong Senior Python Engineer to join the PCORE team and help improve the architecture, reliability, and performance of mission-critical Python services used in production at scale.

Some services were originally developed by Data Science teams with strong domain expertise, and now require additional engineering maturity around scalability, maintainability, observability, and operational excellence.

You will work closely with platform engineers, architects, DevOps, and Data Science teams to analyze existing systems, identify bottlenecks, introduce best practices, and drive technical improvements across the service lifecycle.

Responsibilities

• Analyze and improve performance of Python microservices running in production
• Optimize CPU, memory usage, latency, concurrency, and throughput
• Review existing architecture and propose improvements
• project structure
• testing
• observability
• CI/CD
• reliability
• security
• Work with FastAPI-based services and asynchronous Python code
• Profile and debug production issues under real traffic load
• Improve resiliency and fault tolerance of distributed systems
• Collaborate with Data Science teams to productionize ML-related workloads
• Help define standards and technical direction for Python services inside the organization
• Participate in incident analysis and postmortems when needed

Qualifications

• 5+ years of professional Python development experience
• Strong experience with backend microservices in production environments
• Deep understanding of:
  • FastAPI
  • asyncio
  • concurrency and parallelism
  • multithreading vs multiprocessing
  • packaging tools, pip, uv, C libraries
• Strong knowledge of:
  • profiling and performance optimization
  • memory leak analysis
  • networking, understanding async I/O at OS level, network diagnostics
  • caching strategies
• Experience with:
  • Container optimization, layer caching, multi-stage builds
  • Kubernetes / ECS
  • AWS, IaC
  • Redis / PostgreSQL / MongoDB performance optimization
  • message brokers (RabbitMQ/Kafka)
  • ML libraries, e.g Numpy, Deep Learning frameworks, Feature Engineering
• Strong understanding of distributed systems and system design
• Experience with observability tools:
  • Prometheus
  • Grafana
  • Datadog
  • OpenTelemetry
• Good understanding of production reliability practices:
  • retries
  • circuit breakers
  • backpressure
  • health checks
  • autoscaling
• Experience working with CI/CD pipelines
• Strong communication skills and ability to mentor others
• Experience working with ML/Data Science teams
• Experience optimizing inference services or data pipelines
• Knowledge of gRPC and high-performance APIs
• Experience with load testing and benchmarking tools
• Experience in high-scale environments (24/7 systems, high RPS)
• Contributions to open-source projects

Benefits

• Global Vibes – Collaborate with a worldwide crew.
• Brain Boosters – Learning budgets, access to courses, and tools for your growth.
• Flexible Time Off – We take recharging seriously. Generous leave and wellness policies.
• Agile Everything – Scrum isn’t a buzzword here. It’s how we roll, from product to ops.