Live opening · Posted 8 days ago

Artificial Intelligence Engineer

Sonata Software · Bengaluru, Karnataka, India (Hybrid)
Linkedin No
You are 8 days behind. JobBeeper subscribers saw this role while it was still new.

At a glance

The key details from the original listing.

Posted 8 days ago
CompanySonata Software
LocationBengaluru, Karnataka, India (Hybrid)
Salary2M INR/yr - 2.3M INR/yr
Work modeNo
SourceLinkedin
Listed8 days ago

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About the role

Description supplied by the original job listing.

Cloud AI engineer
Bengaluru
6 - 8 Years
Job Description
8–12 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.

Work arrangement
No

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