Cloud AI Engineer

Mandatory Skills

Artificial Intelligence,AWS,Microsoft Azure

Skill to Evaluate

Artificial Intelligence,AWS,Microsoft Azure

Experience

6 to 8 Years

Location

Bengaluru

Job Description

• 6-8 years of overall experience in software engineering, cloud engineering, AI/ML engineering, or related areas.
• Strong production experience with both AWS and Azure.
• Strong hands-on serverless development and architecture experience.
• Experience delivering production-grade AI/GenAI applications.
• Experience designing event-driven and distributed cloud architectures.
• Strong troubleshooting, system-design, and technical leadership capabilities.
• AI & Generative AI
• Amazon Bedrock and/or Azure OpenAI.
• Azure AI Foundry and Azure AI Search.
• Amazon SageMaker and/or Azure Machine Learning.
• LLMs, embeddings, vector search, RAG, prompt engineering, and AI agents.
• Integration of LLM applications with Lambda/Azure Functions.
• Serverless RAG and event-driven GenAI workflows.
• LLM evaluation, observability, guardrails, and responsible AI.
• Programming & Development
• Strong Python programming skills.
• Experience developing REST APIs using FastAPI, Flask, or equivalent.
• Strong knowledge of JSON, REST, authentication, OAuth/OIDC, and API integration.
• Experience with asynchronous programming and distributed systems.
• Strong understanding of software engineering principles, design patterns, and clean code.
• Cloud, DevOps & MLOps
• Strong hands-on experience with AWS and Azure.
• Docker and Kubernetes experience.
• Terraform, AWS CDK/SAM, or Azure Bicep.
• CI/CD using GitHub Actions, Azure DevOps, Jenkins, GitLab, or equivalent.
• MLOps/LLMOps using MLflow, SageMaker, Azure ML, or equivalent.
• Monitoring and observability using CloudWatch, Azure Monitor, Application Insights, OpenTelemetry, or equivalent.
• Security
• AWS IAM and Azure RBAC/Entra ID.
• Secrets management using AWS Secrets Manager and Azure Key Vault.
• Encryption at rest and in transit.
• VPC/VNet, private endpoints, security groups, and network isolation.
• API authentication, authorization, throttling, and secure API design.
• Understanding of enterprise AI security and data privacy.

Education Qualificaiton

Degree

Job Title

Cloud & AI engineer

Roles & Responsibilities

• Design and implement scalable AI/GenAI solutions across AWS and Azure.
• Develop serverless, 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.
• 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.
• Lead architecture discussions and provide technical guidance to engineering teams.