Cloud AI Engineer

About Saarthee Saarthee is a Global Strategy, Analytics, Technology and AI consulting company, where our passion for helping others fuels our approach and our products and solutions. Our diverse and global team work with one objective in mind: Our Customers’ Success.At Saarthee, we are passionate about guiding organizations towards insights fueled success. That’s why we call ourselves Saarthee–inspired by the Sanskrit word ‘Saarthi’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with offices in UK and India.

Position: Cloud AI Engineer

Location: Bangalore

Work Mode: Hybrid

Min-Max Experience: 6-12 years

Position Summary We are looking for an experienced Cloud & AI Engineer to design, develop, and deploy scalable AI/GenAI solutions across AWS and Microsoft Azure. The role involves serverless architectures, RAG applications, AI agents, cloud-native services, API development, DevOps/MLOps, security, observability, and enterprise AI integrations.

Your Role Responsibilities And Duties

• Design and implement scalable AI/GenAI solutions across AWS and Azure.
• Develop serverless and event-driven AI applications using AWS and Azure native services.
• Build RAG applications, AI agents, LLM-based APIs, and intelligent automation solutions.
• Develop production-grade AI services using Python and serverless compute.
• Design asynchronous and event-driven architectures using queues, events, workflows, and functions.
• Integrate LLM applications with AWS Lambda and Azure Functions.
• Build CI/CD and Infrastructure-as-Code pipelines for cloud and serverless workloads.
• Implement monitoring, logging, security, governance, and cost optimization.
• Integrate AI services with enterprise applications, APIs, databases, and data platforms.
• Develop REST APIs using FastAPI, Flask, or equivalent frameworks.
• Implement secure API authentication, authorization, throttling, and integration.
• Lead architecture discussions and provide technical guidance to engineering teams.

Required Skills And Qualifications

• 6–8 years of experience in Software Engineering, Cloud Engineering, AI/ML Engineering, or related areas.
• Strong hands-on experience with both AWS and Microsoft Azure.
• Strong Python programming and software engineering fundamentals.
• Experience delivering production-grade AI/GenAI applications.
• Strong experience with serverless development and architecture.
• Experience with LLMs, embeddings, vector search, RAG, prompt engineering, and AI agents.
• Experience with Amazon Bedrock and/or Azure OpenAI.
• Experience with Azure AI Foundry and Azure AI Search.
• Experience with Amazon SageMaker and/or Azure Machine Learning.
• Strong understanding of REST APIs, JSON, authentication, OAuth/OIDC, and API integration.
• Experience with asynchronous programming and distributed systems.
• Hands-on experience with Docker and Kubernetes.
• Experience with Terraform, AWS CDK/SAM, or Azure Bicep.
• Experience with CI/CD using GitHub Actions, Azure DevOps, Jenkins, GitLab, or equivalent.
• Knowledge of AWS IAM and Azure RBAC/Entra ID.
• Experience with AWS Secrets Manager and Azure Key Vault.
• Understanding of encryption, VPC/VNet, private endpoints, security groups, and network isolation.
• Strong troubleshooting, system design, analytical, and technical leadership skills.
• BE/B.Tech or Master's degree in Computer Science or related field.