Generative AI Engineer

We are seeking a Generative AI Developer to design, build, deploy, and operate

AI-powered applications natively on AWS . The ideal candidate has strong experience in Python , hands-on expertise with AWS Bedrock (Agent Core SDK) , AWS Strands SDK , and a solid foundation in cloud-native development, DevOps pipelines, and observability .

You will work closely with platform, data, and product teams to deliver secure, scalable, and production-grade GenAI solutions .

Key Responsibilities Generative AI Development

• Design and implement Generative AI applications using AWS Bedrock , including:

o Bedrock Agent Core SDK o Foundation Models (FM) integration Prompt engineering and agent orchestration

• Build AI workflows using AWS Strands SDK for scalable model execution and orchestration
• Develop and maintain reusable AI components, APIs, and services in Python
• Optimize model performance, latency, and cost for production workloads

AWS-Native Application Development

• Design and develop cloud-native applications on 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 architectures

DevOps & CI/CD

• Design and maintain CI/CD pipelines using 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 workloads

Observability & Operations

• Implement end-to-end observability for 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 in incident management , root cause analysis, and system optimization

Security, 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 usage

Required 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 of AWS services and cloud-native design patterns
• Experience building and deploying applications natively on AWS
• CI/CD pipeline implementation and maintenance
• Observability and monitoring in production environments

Preferred 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