- Company Name
- Stefanini North America and APAC
- Job Title
- Python Full Stack Developer
- Job Description
-
**Job title**
Python Full Stack Developer
**Role Summary**
Develop, deploy, and maintain generative AI and cloud‑native applications on Google Cloud Platform (GCP). Collaborate with cross‑functional teams to design end‑to‑end AI solutions, implement CI/CD pipelines, and standardize best practices for scalable, secure, and high‑performance services.
**Expectations**
- 6+ years of professional experience in Python, full‑stack development, and GCP.
- Minimum 3 years as a backend Python engineer with strong software engineering fundamentals.
- 2+ years of cloud engineering experience (GCP, AWS, or Azure).
- Proven ability to work with AI/ML primitives, container orchestration, and IaC.
**Key Responsibilities**
- Deliver generative AI solutions on GCP using Python and modern full‑stack architecture.
- Collaborate with product, engineering, and design teams to scope, build, and ship AI features.
- Design, build, and maintain cloud infrastructure via IaC (Terraform, Cloud Deployment Manager).
- Manage CI/CD ecosystem (Jenkins, Tekton, Cloud Build, GitHub Actions); automate release pipelines.
- Inspect, refactor, and troubleshoot code across the full stack.
- Lead paired programming and test‑driven development practices.
- Innovate with Agentic AI frameworks (LangChain, LangGraph, CrewAI, etc.) and integrate with MLOps tools (Airflow, Kubeflow).
- Mentor teammates on DevOps, Git workflows, and coding standards.
**Required Skills**
- Python (advanced, OOP) – 6+ years
- GCP services: Vertex AI, Cloud Functions/Run, BigQuery, Cloud SQL, Pub/Sub, Firestore, Memorystore, Elasticsearch
- REST API development with FastAPI, Flask, or Django
- Containerization: Docker, Kubernetes (GKE)
- IaC: Terraform
- CI/CD & DevOps: Jenkins, Tekton, Cloud Build, GitHub Actions
- Scripting: Bash, PowerShell
- Version control: GitHub
- MLOps / GenAI foundations; experience with ML workflow orchestration (Airflow, Kubeflow)
- Strong understanding of Agile/Agile‑x practices, TDD, and pair programming
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Computer Engineering, or related technical field
- Preferred: Master’s degree in Computer Science, Machine Learning, or related field
- Certifications: GCP Cloud Architecture or Developer, Docker Certified Associate, Kubernetes Administrator (preferred but not mandatory)