Technical Specialist-App Development

Area(s) of responsibility

Classification: Internal Job Description (Developer) 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: o Bedrock Agent Core SDK o Foundation Models (FM) integration o 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: 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: o AWS CodePipeline / CodeBuild / CodeDeploy o GitHub Actions / GitLab CI (as applicable) • Infrastructure as Code (IaC) using: o 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: o Amazon CloudWatch (logs, metrics, alarms) o AWS X-Ray tracing o Custom metrics for model behavior and performance • Monitor: o Model response latency o Token usage and cost o 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: o Encryption at rest and in transit o Secure secrets management (AWS Secrets Manager / Parameter Store) • Follow enterprise standards for: o 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: o LLMs, RAG (Retrieval Augmented Generation) o Vector databases and embeddings Classification: Internal • Knowledge of containerization: o 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