We are seeking an experienced GenAI Lead / Architect
- to design and implement scalable Generative AI solutions leveraging AWS services. The ideal candidate will lead the transformation of existing LLM-based architectures into efficient, cloud-native platforms, ensuring robust, secure, and cost-effective deployments.
Key Responsibilities :
Design and architect scalable GenAI solutions using AWS Bedrock and other AWS services.Lead the transformation of homegrown LLM-based architecture into a managed cloud-native solution.Provide architectural guidance across components : RAG pipelines, LLM orchestration, vector DB integration, inference workflows, and scalable endpoints.Collaborate closely with GenAI developers, MLOps, and data engineering teams to ensure alignment on implementation.Evaluate, integrate, and benchmark frameworks such as LangChain, Autogen, Haystack, or LlamaIndex.Ensure infrastructure and solutions are secure, scalable, and cost-optimized on AWS.Act as a technical SME and hands-on contributor for architecture reviews and POCs.Must-Have Skills :
Proven experience architecting LLM applications with RAG, embeddings, prompt engineering.Hands-on understanding of frameworks like LangChain, LlamaIndex, or Autogen.Knowledge of LLMs like Anthropic Claude, Mistral, Falcon, or custom models.Strong understanding of API design, containerization (Docker), and serverless architecture.Expertise with AWS Bedrock, S3, Lambda, SageMaker, API Gateway, DynamoDB / Redshift, etc.Experience leading cloud-native transformations.Preferred :
AWS Certified Solutions Architect.Experience with CI / CD, DevOps integration for ML / AI pipelines.Exposure to Azure / GCP in GenAI (bonus).Skills Required
S3, Lambda, MLops, data engineering