WeyBee Solutions Pvt. Ltd.
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Principal / Staff Software Engineer

Principal / Staff Software Engineer

Principal / Staff Software Engineer

Backend  •  MLOps  •  Cloud Infrastructure  |   10+ Years  |  Full-time

Role Overview

We are looking for a Principal / Staff Software Engineer with deep expertise in Python, backend systems, MLOps, and cloud infrastructure. You will design, build, and scale production-grade platforms, lead technical architecture, establish engineering best practices, and deliver reliable, high-performance cloud-native solutions.

Key Areas of Expertise

  • Python software development
  • Backend, microservices, and distributed systems architecture
  • MLOps and machine learning infrastructure
  • Cloud infrastructure and networking — AWS, VPCs, DNS, ingress, and service mesh
  • Web application development
  • Database design and optimization
  • CI/CD, DevOps, and automation
  • Docker and Kubernetes — containerization, orchestration, and deployment
  • Observability — Datadog, Prometheus, Grafana, ELK/OpenSearch, and distributed tracing
  • System scalability, reliability, and performance
  • Technical leadership and mentoring

Responsibilities

  • Architect and build scalable Python backend services, APIs, and distributed systems.
  • Design and operate end-to-end ML infrastructure — pipelines, model registry, serving, and monitoring.
  • Own AWS cloud infrastructure: VPCs, EKS, IAM, networking, and service mesh.
  • Manage Kubernetes clusters and containerized workloads in production.
  • Build and maintain CI/CD pipelines and infrastructure-as-code (Terraform/Pulumi).
  • Set up and maintain observability stacks and drive SLO/reliability engineering.
  • Lead code reviews, define engineering standards, and mentor engineers.
  • Design and optimize relational and non-relational database schemas and query performance

Requirements

  • 10+ years of software engineering experience with significant time in senior or staff-level roles.
  • Expert-level Python — FastAPI, async, testing, and performance optimization.
  • Hands-on MLOps experience: MLflow, Kubeflow, Airflow, or equivalent; model serving with TorchServe, Triton, or BentoML.
  • Advanced AWS — EKS, EC2, RDS, S3, Lambda, VPC design, IAM, and CloudFront.
  • Production Kubernetes — Helm, autoscaling, network policies, and RBAC.
  • CI/CD and IaC — GitHub Actions, Terraform or Pulumi, GitOps with ArgoCD or FluxCD.
  • Strong observability toolkit — Datadog, Prometheus, Grafana, OpenTelemetry, ELK/OpenSearch.
  • Database proficiency — PostgreSQL, Redis, MongoDB; query tuning and schema design.
  • Strong communication skills and ability to lead technical discussions with engineering and non-engineering stakeholders.