Senior AI Engineer

We are seeking a highly skilled Senior AI Engineer with hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) systems in production environments. The ideal candidate will have deep expertise in Python, strong exposure to AWS AI/ML services (especially Amazon Bedrock), and the ability to architect scalable, cloud-native AI solutions.

• Design, build, and deploy RAG-based AI systems (including multimodal where applicable).
• Implement advanced LLM prompting strategies, context management, and hallucination mitigation techniques.
• Develop scalable backend services in Python.
• Architect and integrate AI workflows using Amazon Bedrock (FMs, embeddings, Guardrails, Agents).
• Design and optimize retrieval systems (chunking, metadata tagging, hybrid retrieval, reranking, citation support).
• Build and manage data pipelines on AWS ensuring data quality, lineage, and versioning.
• Implement event-driven architectures using AWS Lambda, API Gateway, Step Functions, EventBridge, SQS/SNS.
• Design secure and scalable data access patterns using DynamoDB, S3, OpenSearch/vector databases.
• Enforce best practices in IAM least privilege, KMS encryption, Secrets Manager, CloudTrail auditing.
• Implement CI/CD pipelines and Infrastructure as Code using Terraform, CloudFormation, or CDK.
• Apply production reliability patterns such as rate limiting, retries, caching, circuit breakers, and disaster recovery awareness.

• Strong Python engineering experience with production deployments.
• Hands-on implementation experience with RAG systems (at least one production-grade deployment).
• Deep expertise in AWS services, including:
• Amazon Bedrock (FMs, embeddings, Guardrails, Agents)
• AWS Lambda
• DynamoDB (schema design & access patterns)
• S3 (bucket architecture & event-driven ingestion)
• Amazon Kendra (enterprise search / hybrid retrieval)
• Proven knowledge of:
• LLM architectures and prompting patterns
• Hybrid search and vector database implementations
• Data engineering workflows on AWS
• Experience building secure, scalable cloud-native systems.
• Strong problem-solving skills and clarity in technical communication.
• AWS Machine Learning Specialty certification (or equivalent AI/ML certification) is required.