AWS Generative AI Engineer

• Design, develop, and deploy Generative AI solutions leveraging Amazon Bedrock, Anthropic Claude, and other foundation models.
• Build and optimize RAG (Retrieval-Augmented Generation) architectures using vector databases and enterprise knowledge sources.
• Develop AI-powered applications such as chatbots, virtual assistants, document processing, content generation, and intelligent search solutions.
• Create and optimize prompts, workflows, and model configurations to improve response quality, accuracy, and performance.
• Integrate Bedrock foundation models with enterprise applications, APIs, and AWS services.
• Implement scalable and secure cloud-native solutions using AWS services such as Lambda, API Gateway, ECS, EKS, S3, DynamoDB, and OpenSearch.
• Finetune model outputs through prompt engineering, guardrails, and evaluation frameworks.
• Collaborate with data engineers, architects, product owners, and business stakeholders to identify GenAI use cases and deliver solutions.
• Monitor model performance, costs, latency, and security compliance.
• Ensure adherence to responsible AI practices, governance, and security standards.
• Stay updated with emerging trends in Generative AI, LLMs, and AWS AI/ML services.

• Strong experience with AWS Cloud Services.
• Hands-on experience with Amazon Bedrock, AWS Lambda, API Gateway, Amazon S3, Amazon DynamoDB, Amazon OpenSearch, ECS, EKS, CloudWatch, and IAM.
• Strong experience with Amazon Bedrock and Anthropic Claude models.
• Solid understanding of Large Language Models (LLMs), prompt engineering, RAG architecture, vector databases, AI agents and agentic workflows, finetuning and model evaluation, responsible AI, and AI governance.
• Proficiency in Python.
• Experience with LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, and SDK integrations.
• Experience integrating structured and unstructured data sources.
• Knowledge of embeddings, semantic search, knowledge bases, and document ingestion pipelines., * Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• AWS certifications such as AWS Certified, AWS Certified Machine Learning Engineer, or AWS AI Practitioner.
• Experience with MLOps, CI/CD, and infrastructure-as-code tools like Terraform and CloudFormation.
• Familiarity with other LLM providers such as OpenAI, Meta, Llama, Mistral, or Cohere.

Skills:

• Solution Design and Architecture.
• Generative AI and LLM Expertise.
• Cloud-Native Development.
• Problem Solving and Analytical Thinking.
• Stakeholder Management.
• Innovation Mindset.
• Agile Delivery.
• Communication and Collaboration Skills.

Education and Experience:

• 5+ years of overall software/cloud development experience.
• 2+ years of hands-on experience in Generative AI and LLM-based solution development.
• Proven experience delivering enterprise-scale AI solutions on AWS.

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