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.
Programming
Technical Skill Set :
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.
(ref:hirist.tech)
