Cloud AI Engineer

Job Description :

We are seeking an experienced Cloud AI Engineer with 5+ years of experience in designing, developing, and deploying AI/ML solutions on cloud platforms. The ideal candidate will have expertise in Generative AI, Large Language Models (LLMs), cloud-native AI services, MLOps, and modern application development. The role involves building scalable AI-powered applications, deploying machine learning models, integrating AI services into enterprise systems, and collaborating with cross-functional teams to deliver innovative AI solutions.

Key Responsibilities :

- Design, develop, and deploy AI/ML and Generative AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).

- Build and deploy scalable applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks.

- Develop backend APIs and AI services using Python (FastAPI, Flask) or Node.js.

- Integrate cloud AI services such as Azure OpenAI, Amazon Bedrock, Vertex AI, Azure AI Foundry, or similar platforms into enterprise applications.

- Design and implement AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or CrewAI.

- Build and optimize vector search solutions using databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.

- Develop, deploy, and monitor machine learning models using MLOps best practices.

- Create CI/CD pipelines for AI applications and automate model deployment and monitoring.

- Containerize AI workloads using Docker and orchestrate deployments using Kubernetes.

- Implement secure, scalable, and highly available cloud-native AI architectures.

- Optimize AI applications for performance, latency, cost, and scalability.

- Collaborate with data scientists, software engineers, DevOps teams, and business stakeholders to deliver production-ready AI solutions.

- Troubleshoot production issues, conduct root cause analysis, and implement long-term improvements.

- Stay updated with emerging AI technologies, cloud services, and industry best practices.

Required Skills :

- 5+ years of experience in AI/ML engineering, cloud application development, or software engineering.

- Strong proficiency in Python and SQL.

- Experience building and deploying AI/ML applications in production environments.

- Hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent workflows.

- Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or CrewAI.

- Strong knowledge of cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP).

- Experience with cloud AI services such as Azure OpenAI Service, Azure AI Foundry, Amazon Bedrock, Google Vertex AI, or similar managed AI platforms.

- Hands-on experience with vector databases such as Pinecone, Weaviate, ChromaDB, Milvus, or FAISS.

- Experience developing REST APIs using FastAPI, Flask, or Node.js.

- Knowledge of machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.

- Experience with Docker, Kubernetes, CI/CD pipelines, and Infrastructure as Code (Terraform or CloudFormation).

- Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Azure Machine Learning, or Vertex AI Pipelines.

- Understanding of application security, identity management, and responsible AI practices.

- Strong analytical, problem-solving, and communication skills.

Preferred Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

- AWS Certified Machine Learning Specialty, Microsoft Azure AI Engineer Associate, Google Professional Machine Learning Engineer, or equivalent cloud certification is preferred.

- Experience with event-driven architectures, streaming platforms (Kafka, Pub/Sub), and distributed systems is an added advantage.

- Familiarity with monitoring and observability tools such as Prometheus, Grafana, Azure Monitor, or CloudWatch is desirable.

- Experience working in Agile/Scrum environments and delivering enterprise-scale AI transformation projects.