Generative AI Engineer

Location:

Hyderabad, Bangalore, Noida, Chennai and Pune

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, Dev Ops 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, Dynamo

DB, Aurora, Open Search

- Implement secure IAM roles and policies aligned with least-privilege principles
- Build event-driven and microservices-based architectures

Dev Ops & CI/CD

- Design and maintain CI/CD pipelines using tools such as:
- AWS Code Pipeline / Code Build / Code Deploy o Git Hub Actions / Git Lab CI (as applicable)
- Infrastructure as Code (IaC) using:
- AWS Cloud Formation / CDK / Terraform
- Automate build, test, deployment, and rollbacks for GenAI workloads

Observability & Operations

- Implement end-to-end observability for AI and application workloads:
- Amazon Cloud Watch (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