Sonata Software
Cloud AI Engineer
Designs and builds production-grade AI/GenAI applications across AWS and Azure using Python and serverless, event-driven architectures (Lambda/Azure Functions), including RAG, LLM agents, and APIs, plus CI/CD, IaC, MLOps, observability, and cloud security. Role is based in Bengaluru for engineers with 6-8 years of experience.
- Compensation
- Not disclosed
- Location
- Bengaluru
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 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
- 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
- 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
- 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
- Understanding of software engineering principles, design patterns, and clean code
- 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
Full description
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.