About the Role :

We are seeking a highly skilled AI Application Backend Developer with strong expertise in Python and Google Cloud Platform (GCP) to design, build, and scale AI-driven backend systems.

This role focuses on developing production-grade AI applications, building scalable APIs, integrating LLMs and ML models, and deploying cloud-native solutions on GCP. You will collaborate closely with AI engineers, data scientists, frontend developers, and DevOps teams to deliver intelligent, reliable, and high-performance backend services.

The ideal candidate has hands-on experience in building AI-enabled systems using modern Python frameworks and cloud infrastructure, with strong knowledge of distributed systems and scalable architecture.

Key Responsibilities :

AI Application Development :

- Design and develop backend services to power AI-driven applications.

- Integrate Large Language Models (LLMs), ML models, or AI services into production systems.

- Build RESTful APIs and microservices using Python frameworks (FastAPI, Flask, Django).

- Implement RAG (Retrieval-Augmented Generation) pipelines and AI orchestration workflows where applicable.

- Optimize AI inference performance, latency, and reliability.

Cloud & Infrastructure (GCP) :

- Design and deploy AI backend services on Google Cloud Platform (GCP).

- Work with GCP services such as: 1. BigQuery 2. Cloud Run 3. Cloud Functions 4. Compute Engine 5. GKE (Kubernetes Engine) 6. Cloud Storage 7. Vertex AI (preferred).

- Ensure scalability, monitoring, and fault tolerance of cloud applications.

- Implement IAM policies, security best practices, and environment isolation.

Data & Integration :

- Develop data pipelines to support AI models and analytics workflows.

- Integrate backend systems with third-party APIs and enterprise applications.

- Work with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, BigQuery).

- Handle data validation, transformation, and preprocessing logic.

DevOps & CI/CD :

- Containerize applications using Docker.

- Deploy and manage services using Kubernetes (GKE preferred).

- Implement CI/CD pipelines (GitHub Actions, Cloud Build, Jenkins).

- Monitor application health and performance using logging and observability tools.

Collaboration & Engineering Excellence:

- Participate in Agile/Scrum ceremonies.

- Write clean, maintainable, well-documented code.

- Conduct peer code reviews.

- Troubleshoot and debug production issues.

- Contribute to architectural decisions and continuous improvement.

Technical Skill Set :

Programming :

- Python (Advanced)

- SQL

Frameworks :

- FastAPI / Flask / Django

- Async programming (asyncio)

Cloud :

- Google Cloud Platform (GCP)

- Vertex AI (preferred)

- BigQuery

- Cloud Run / GKE

DevOps :

- Docker

- Kubernetes

- CI/CD pipelines

- Git

AI/ML :

- LLM integrations

- RAG pipelines

- Prompt engineering basics

- Embedding & vector databases (Pinecone, FAISS, etc.)

Qualifications :

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Engineering, or related field.

- 6+ years of backend development experience.

- Strong proficiency in Python.

- Hands-on experience with GCP cloud services.

- Experience building scalable backend systems and APIs.

- Knowledge of microservices architecture.

- Strong understanding of REST APIs and asynchronous programming.

- Experience with SQL-based databases.

- Familiarity with containerization (Docker) and cloud-native deployment.

- Strong analytical and problem-solving skills.

Preferred Qualifications :

- Experience with AI/ML frameworks (LangChain, Hugging Face, TensorFlow, PyTorch).

- Experience with Vertex AI or GCP AI services.

- Experience building LLM-based applications (RAG, Agents, embeddings).

- Experience with message queues (Pub/Sub, Kafka).

- Knowledge of MLOps best practices.

- GCP certification (Professional Cloud Developer / Data Engineer / ML Engineer).

- Experience in high-scale, enterprise-grade AI systems.