Gen AI Lead

Key Responsibilities

Generative AI Development

Design and implement Generative AI applications using AWS Bedrock, including: Bedrock Agent Core SDK

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

Classification: Internal

AWS-Native Application Development

Design and develop cloud-native applications on AWS using: AWS Lambda, ECS/EKS, EC2

API Gateway / Application Load Balancer

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
• 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)
• AWS X-Ray tracing
• Custom metrics for model behavior and performance
• Monitor: Model response latency
• Token usage and cost
• 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
• Secure secrets management (AWS Secrets Manager / Parameter Store)
• Follow enterprise standards for: Data privacy
• AI governance
• Responsible AI usage

Required Skills & Qualifications

Technical Skills (Must Have)

• Python (advanced proficiency)

Hands-on experience with: AWS Bedrock

AWS Bedrock Agent Core SDK

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 principlesRole & responsibilities

Preferred candidate profile