Job title- Cloud and AI

Minimum Experience

6

Maximum Experience

8

Mandatory Skills

Artificial Intelligence, AWS,Microsoft Azure

Skill to Evaluate

Artificial Intelligence, AWS,Microsoft Azure

Experience

6 to 8 Years

Location

Bengaluru

Work mode- Hybrid

- 6-8 years of overall experience in software engineering, cloud engineering, AI/ML engineering, or related areas.
- Solid 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.

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.

Interested candidates can apply.

📌 Cloud and AI (Bengaluru)
🏢 Orcapod Consulting Services
📍 Bengaluru