Job Title

We are seeking aGenerative AI Developerto design, build, deploy, and operate AI-powered applications natively on AWS . The ideal candidate has strong experience inPython , hands-on expertise withAWS Bedrock (Agent Core SDK) ,AWS Strands SDK , and a solid foundation incloud-native development, DevOps pipelines, and observability . You will work closely with platform, data, and product teams to deliversecure, scalable, and production-grade GenAI solutions .Key Responsibilities Generative AI Development Design and implementGenerative AI applicationsusingAWS Bedrock , including: o Bedrock Agent Core SDK o Foundation Models (FM) integration o Prompt engineering and agent orchestration Build AI workflows usingAWS Strands SDKfor scalable model execution and orchestration Develop and maintain reusableAI components, APIs, and servicesin Python Optimize model performance, latency, and cost for production workloadsAWS-Native Application Development Design and developcloud-native applicationson AWS using: o AWS Lambda, ECS/EKS, EC2 o API Gateway / Application Load Balancer o S3, DynamoDB, Aurora, OpenSearch Implement secure IAM roles and policies aligned with least-privilege principles Build event-driven and microservices-based architecturesDevOps & CI/CD Design and maintainCI/CD pipelinesusing tools such as: AWS CodePipeline / CodeBuild / CodeDeploy o GitHub Actions / GitLab CI (as applicable) Infrastructure as Code (IaC) using: AWS CloudFormation / CDK / Terraform Automate build, test, deployment, and rollbacks for GenAI workloadsObservability & Operations Implement end-to-endobservabilityfor AI and application workloads: Amazon CloudWatch (logs, metrics, alarms) o AWS X-Ray tracing o Custom metrics for model behavior and performance Monitor: Model response latency o Token usage and cost o Error rates and failure scenarios Participate inincident management , root cause analysis, and system optimizationSecurity, Governance & Compliance Ensure secure handling of data used in AI workflows Implement: Encryption at rest and in transit o Secure secrets management (AWS Secrets Manager / Parameter Store) Follow enterprise standards for: Data privacy o AI governance o Responsible AI usageRequired Skills & Qualifications Technical Skills (Must Have)•Python(advanced proficiency) Hands-on experience with: o AWS Bedrock o AWS Bedrock Agent Core SDK o AWS Strands SDK Strong knowledge ofAWS servicesand cloud-native design patterns Experience building and deploying applicationsnatively on AWS CI/CD pipeline implementation and maintenance Observability and monitoring in production environmentsPreferred Skills (Good to Have) Experience with: LLMs, RAG (Retrieval Augmented Generation) Vector databases and embeddings Knowledge of containerization: Docker, Kubernetes (EKS) Familiarity with MLOps or Model Lifecycle Management Experience with cost optimization for AI workloads Understanding of ethical AI and responsible AI principles