Senior FullStack (UI + Python) Developer

• *Role & responsibilities

As a Senior FullStack Developer with 6 to 12 years of experience, you will act as a technical leader and core contributor to our engineering initiatives. Your primary responsibilities will include:

• Architecture & Development: Lead the design, development, and deployment of scalable, high-performance FullStack applications and microservices.
• API Design: Architect and build secure, fast, and reliable RESTful APIs using FastAPI.
• UI Design: Conceptualize and develop responsive, user-friendly, and accessible user interfaces using modern JavaScript frameworks (e.g., Angular, React, Vue.js).
• System Integration: Drive seamless Python integrations, connecting diverse internal applications, legacy systems, and external third-party APIs/SaaS platforms.
• Cloud Native Engineering: Deploy, optimize, and manage applications within the Google Cloud Platform (GCP) ecosystem, ensuring high availability and fault tolerance.
• Technical Leadership: Mentor mid-level and junior engineers, enforce coding standards, conduct rigorous code reviews, and advocate for engineering best practices.
• Cross-Functional Collaboration: Work closely with product managers, data engineers, and cloud architects to translate complex business requirements into robust technical solutions.
• *Technical Requirements
• Core Experience: 6 to 12 years of hands-on software engineering experience, with a heavy emphasis on backend development using Python.
• Frameworks: Extensive experience building backend services using FastAPI (experience with data validation, dependency injection, and asynchronous programming).
• Front-End Proficiency: Hands-on experience and demonstrable skill in utilizing modern JavaScript frameworks, such as React or Angular, to build responsive, scalable, and highly interactive user experiences.
• Python Libraries: Deep proficiency with standard and foundational Python libraries, including but not limited to Pydantic, SQLAlchemy, Requests, Pytest, as well as data-manipulation libraries like Pandas and NumPy.
• Integration Expertise: Proven track record in system integrationworking with enterprise databases (SQL/NoSQL), message brokers (e.g., Kafka, GCP Pub/Sub), and building robust API-to-API communication layers.
• Cloud Platforms: Solid hands-on knowledge of Google Cloud Platform (GCP). Familiarity with deploying applications using GCP services (e.g., Cloud Run, Cloud Functions, GKE, Compute Engine, or App Engine).
• *Software Engineering Practices: Strong grasp of version control (Git), containerization (Docker, Kubernetes), and modern CI/CD pipelines.
• *Good To Have
• GCP Certifications: Holding a Google Cloud Professional Developer or Cloud Architect certification.
• Alternative Frameworks: Working knowledge of other popular Python frameworks like Flask or Django.
• Data/AI Exposure: Background or foundational understanding of Data Engineering (ETL pipelines, BigQuery) or integrating Machine Learning models into production environments.
• Agile/Scrum: Experience thriving in an Agile work environment focused on pragmatic delivery and rapid iteration.
• Experience in writing code using tools such as Claude, Cursor, Co-Pilot etc.