Python AI/Cloud Developer

• Design, develop, and maintain scalable backend services and APIs using Python.
• Build and optimize microservices-based applications for cloud environments.
• Develop and integrate AI/LLM-powered solutions using frameworks such as LangChain and LangGraph.
• Deploy, manage, and monitor applications on Kubernetes platforms.
• Leverage cloud services within AWS and/or Google Cloud Platform to build secure and scalable solutions.
• Work with cloud-native tools such as BigQuery, Airflow, GKE, Lambda, ECS/EKS, Cloud Functions, or equivalent services.
• Collaborate with data engineers, architects, product teams, and business stakeholders to deliver enterprise-grade solutions.
• Implement CI/CD pipelines and DevOps best practices for application deployment and monitoring.
• Troubleshoot performance issues and optimize applications for scalability and reliability.
• Participate in architecture discussions and contribute to technical design decisions.

We are seeking a highly skilled Senior Python AI/Cloud Developer to design, develop, and deploy scalable enterprise applications and AI-powered solutions. The ideal candidate will have strong expertise in Python-based service development, cloud-native technologies, Kubernetes, and foundational knowledge of Large Language Model (LLM) frameworks. This role will be responsible for building robust backend services, integrating AI capabilities, and deploying cloud-native applications in AWS or Google Cloud Platform environments., * 5+ years of experience in software development with strong hands-on Python expertise.

• Extensive experience building RESTful APIs and backend services using Python frameworks such as FastAPI, Flask, or Django.
• Hands-on experience developing and deploying microservices architectures.
• Experience working in AWS and/or Google Cloud Platform cloud environments.
• Strong understanding of Kubernetes and container orchestration.
• Experience with cloud services including:
• Google Cloud Platform: BigQuery, Airflow (Cloud Composer), GKE
• AWS: EKS, Lambda, ECS, S3, CloudWatch
• Understanding of AI/LLM concepts and practical exposure to LangChain and LangGraph.
• Experience with Git, CI/CD pipelines, and DevOps practices.
• Strong problem-solving and analytical skills.

Preferred Qualifications

• Experience implementing Generative AI use cases in enterprise environments.
• Knowledge of Vector Databases, RAG (Retrieval Augmented Generation), and AI agent frameworks.
• Familiarity with infrastructure-as-code tools such as Terraform.
• Experience with monitoring and observability tools such as Prometheus, Grafana, DataDog, or Cloud Monitoring.
• Exposure to MLOps and AI deployment best practices.
• Experience working in Agile/Scrum environments.