Technical Specialist-App Development

Area(s) of responsibility

Classification: Internal

Role Summary
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:
oBedrock Agent Core SDK
oFoundation Models (FM) integration
oPrompt 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:
oAWS Lambda, ECS/EKS, EC2
oAPI Gateway / Application Load Balancer
oS3, 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:
oAWS CodePipeline / CodeBuild / CodeDeploy
oGitHub Actions / GitLab CI (as applicable)
•Infrastructure as Code (IaC) using:
oAWS CloudFormation / CDK / Terraform
•Automate build, test, deployment, and rollbacks for GenAI workloads
Observability & Operations
•Implement end-to-end observability for AI and application workloads:
o
Amazon CloudWatch (logs, metrics, alarms)
o
AWS X-Ray tracing
o
Custom metrics for model behavior and performance
•Monitor:
oMdel response latency
oToken usage and cost
oError rates and failure scenarios
•Participate in incident management, root cause analysis, and system optimization
Classification: Internal
Security, Governance & Compliance
•Ensure secure handling of data used in AI workflows
•Implement:
oEncryption at rest and in transit
oSecure secrets management (AWS Secrets Manager / Parameter Store)
•Follow enterprise standards for:
oData privacy
oAI governance
oResponsible AI usage
Required Skills & Qualifications
Technical Skills (Must Have)
•Python (advanced proficiency)
•Hands-on experience with:
oAWS Bedrock
oAWS Bedrock Agent Core SDK
oAWS 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:
oLLMs, RAG (Retrieval Augmented Generation)
Classification: Internal
oVector databases and embeddings
•Knowledge of containerization:
oDocker, Kubernetes (EKS)
•Familiarity with MLOps or Model Lifecycle Management
•Experience with cost optimization for AI workloads
•Understanding of ethical AI and responsible AI principles