AI Engineer
altcloudai- Posted 2 hours ago
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Job Description
About the Company ALTCloudAI is building the future of intelligent, cloud-native enterprises. We combine AI-forward solutions with deep cloud engineering expertise to help organizations create secure, scalable, automated, and future-ready platforms.
We are scaling fast and are expanding our team in the India with AI Engineering positions.
Location: Hyderabad
Experience: 1-4 years
Joining: Immediate Joiners only (less than 3 weeks)
Work that you would be part of
Build GenAI systems that run in production, not POCs — work alongside experts on RAG pipelines, intelligent document processing, and AI-powered workflows on Bedrock, SageMaker, and beyond, deployed for enterprise clients in regulated environments where accuracy, security, and auditability actually matter
Work in an AI-native engineering team — we use AI-assisted development and MCP-based tooling day to day, so you will be shipping software the way modern engineering teams increasingly do
What we are looking for
- 1-4 years of experience
- Strong understanding of RAG architectures, agentic workflows, vector databases, model integration, and LLM application optimization.
- Production GenAI experience with Amazon Bedrock, Langchain /Langraph, SageMaker and/or equivalent platforms; hands-on experience with RAG, embeddings, vector stores, prompt engineering and AI agents/AgentCore.
- Strong Python development skills, with experience building production-grade AI/ML applications and APIs.
- AWS Certification(s) such as Developer, Solutions Architect, Machine Learning or Generative AI Engineer would be preferred.
Good To have
- Strong hands-on AWS experience, particularly serverless and cloud-native services such as Lambda, API Gateway, DynamoDB, Step Functions, EventBridge and S3.
- IaC and DevOps fluency using CDK/Terraform, CI/CD pipelines, containerization and production deployment practices.
Apply via LinkedIn || OR send your profile to [Confidential Information]
www.altcloudai.com
More Info
Key Skills
RAG embeddings
Langchain
vector databases
LLM application optimization
EventBridge
IaC
cloud-native services
Langraph
production deployment practices
RAG architectures
AgentCore
model integration
prompt engineering
agentic workflows
SageMaker
vector stores
CI/CD pipelines
AI agents
Amazon Bedrock




