Company Name

Birlasoft ( Pune )

Job Description

• Roles and Responsibilities:
  • Provide technical leadership and architectural direction for building and operating production-grade Generative AI solutions on AWS.
  • Design and implement Generative AI applications using AWS Bedrock.
  • Work with AWS Bedrock Agent Core SDK and integrate Foundation Models.
  • Perform prompt engineering and agent orchestration.
  • Build scalable AI workflows using AWS Strands SDK (multi-agent systems, LangGraph, CrewAI).
  • Develop and maintain reusable AI components, APIs, and services using Python.
  • Optimize model performance, response latency, token usage, and cost for production workloads.
  • Support real-world enterprise use cases beyond POCs and demos.
  • Design and develop cloud-native applications on AWS.
  • Work with AWS Lambda, ECS, EKS, and EC2 services.
  • Implement APIs using API Gateway and Application Load Balancer.
  • Use S3, DynamoDB, Aurora, and OpenSearch for data storage and search.
  • Build event-driven and microservices-based architectures.
  • Implement secure IAM roles and policies following least-privilege principles.
  • Design and maintain CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, GitHub Actions, and GitLab CI.
  • Implement Infrastructure as Code using AWS CloudFormation, CDK, and Terraform.
  • Automate build, test, deployment, and rollback processes for GenAI workloads.
  • Implement end-to-end observability using Amazon CloudWatch and AWS X-Ray.
  • Create custom metrics to monitor model behavior and performance.
  • Monitor model response latency, token usage, cost, and error rates.
  • Participate in incident management, root cause analysis, and system optimization.
  • Ensure secure handling of data used in AI workflows.
  • Implement encryption at rest and in transit.
  • Manage secrets using AWS Secrets Manager and Parameter Store.
  • Follow enterprise standards for data privacy, AI governance, and responsible AI usage.
  • Possess strong hands-on experience with AWS Bedrock, AWS Bedrock Agent Core SDK, and AWS Strands SDK.
  • Demonstrate advanced proficiency in Python.
  • Have a strong understanding of LLMs, embeddings, prompts, tokens, latency, and cost factors.
  • Have practical experience with RAG architectures, vector databases, and grounding strategies.
  • Be experienced in building and deploying AWS-native applications.
  • Have strong knowledge of AWS services and cloud-native design patterns.

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