Cloud AI Consultant

Saarthee; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Saarthee in Bengaluru is seeking an experienced Cloud & AI Engineer to design, develop, and deploy scalable AI/GenAI solutions across AWS and Azure. The role covers serverless architectures, RAG applications, AI agents, cloud-native services, API development, DevOps/MLOps, security, observability, and enterprise AI integrations.

You will lead architecture discussions, implement production-grade AI services in Python, build CI/CD pipelines, and ensure observability and cost optimization while

Qualifications

• 6-8 years of experience in software/cloud/AI engineering.
• Strong hands-on experience with AWS and Azure.
• Proficient in Python programming and software engineering fundamentals.
• Experience with serverless development and architecture.
• Experience with LLMs, embeddings, vector search, and RAG.
• Experience with Bedrock/Azure OpenAI and AI services.
• Familiarity with security, observability, and API integration.

Responsibilities

• Design and implement scalable AI/GenAI solutions on AWS and Azure.
• Develop serverless AI applications using native cloud services.
• Build RAG apps, AI agents, LLM-based APIs, and automation.
• Develop production-grade AI services using Python and serverless compute.
• Design event-driven architectures using queues, events, and functions.
• Integrate LLM apps with AWS Lambda and Azure Functions.
• Establish CI/CD and IaC pipelines for cloud workloads.
• Implement monitoring, security, governance, and cost optimization.
• Integrate AI services with enterprise apps, APIs, and data platforms.
• Develop REST APIs with FastAPI, Flask, or similar.
• Lead architecture discussions and guide engineering teams.

Skills

AWS/Azure experience

Python

Serverless architecture

LLMs/RAG

Docker/Kubernetes

CI/CD

REST APIs

Distributed systems

Education

BE/B.Tech or MSc CS

Tools

Docker

Kubernetes

Terraform

AWS CDK/SAM

Azure Bicep

GitHub Actions

Azure DevOps

Job description

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 Skillsand 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.
• 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.