Principal Staff Software Engineer

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.