Generative AI Technical Specialist-App Development

Long Description

Generative AI Developer (AWS-Native)
Location Hyderabad / Hybrid / Remote (as applicable)
Experience 5–10 years (with hands-on GenAI experience preferred)
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:
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
Classification: Internal
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

Area(s) of responsibility