Aws Devops Architect

Full Stack AI Engineer to design build and deploy end to end AIML powered applications from frontend interfaces to cloud native backend infrastructure with a strong emphasis on AWS as the primary platform for model hosting orchestration and data pipelines

Key Responsibilities

• Design and implement LLM based applications RAG pipelines agentic workflows finetuning prompt engineering
• Integrate foundation models via Amazon Bedrock and manage model selection guardrails and evaluation
• Build and optimize vector search and retrieval pipelines Amazon OpenSearch Kendra or thirdparty vector DBs like Pinecone on AWS
• Implement agent orchestration frameworks LangChain LangGraph Bedrock Agents for multistep reasoning tasks
• Build scalable APIs and microservices using Python FastAPIFlask or Nodejs
• Implement data pipelines with AWS Glue EMR or native Python ETL for traininginference data prep
• Manage containerized workloads via ECSEKS
• Build responsive UIs that consume backend AI services
• Implement realtime streaming responses for chatstyle AI interfaces
• Integrate authentication Amazon Cognito and rolebased access control
• Architect solutions using core AWS services Bedrock SageMaker Lambda API Gateway S3 DynamoDB RDSAurora ECSEKS Step Functions
• Set up CICD pipelines CodePipeline CodeBuild or GitHub Actions AWS deploy
• Manage cost optimization for AI workloads token usage monitoring model routing caching strategies via Elasti Cache.

Required Skills

Category Skills

• Cloud AWSBedrock Lambda API Gateway S3 DynamoDB ECSEKS Step Functions IAM CloudFormationCDKTerraform
• AIMLLLM integration RAG prompt engineering LangChainLangGraph embeddings vector databases
• BackendPython strong FastAPIFlask RESTGraphQL API design
• FrontendReactNextjs or Streamlit TypeScriptJavaScript
• DevOpsCICD Docker containerization Git
• DataSQLNoSQL basic ETL S3 data lake patterns

Mandatory Skills : Amazon Bedrock, AWS Lambda, CI/CD Architecture, GenAI - LLMOps, Python

Good to Have Skills : Docker, Java, MySQL, React