Lead AI Engineer

• Design and implement end-to-end AI/ML solutions, including LLM-based applications
• Build RAG pipelines using vector databases and enterprise data sources
• Build machine learning models with automated training, validation, monitoring, and retraining
• Develop APIs and services to operationalize AI capabilities across the organization
• Build ingestion for multimodal content and transformation pipelines for structured and unstructured data
• Integrate AI workflows with enterprise systems such as policy, claims, and billing systems
• Ensure data quality, traceability, reliability, and governance in AI pipelines
• Implement CI/CD for AI/ML workflows
• Deploy, monitor, and maintain models in production
• Manage model versioning, performance monitoring, and retraining processes
• Develop solutions using Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related AWS services
• Contribute to the evolving use of AWS Bedrock
• Implement LLM guardrails including grounding, validation, and safety
• Ensure secure handling of sensitive data such as PII and financial data
• Build systems aligned with enterprise governance and compliance standards

• 10+ years in software or data engineering
• 5 years of AI/ML engineering experience
• Hands-on experience building production AI/ML systems
• Experience with RAG pipelines, LLMs, or NLP-based systems
• Experience with AWS Bedrock or similar GenAI platforms
• Experience with data pipelines and distributed systems
• Experience deploying and operating systems in AWS
• Working knowledge of MLOps practices, including CI/CD, monitoring, and versioning
• Preferred: Experience with vector databases such as Pinecone or Weaviate
• Preferred: Experience in regulated industries such as insurance, finance, or healthcare
• Preferred: Exposure to microservices and containerized environments such as Docker and Kubernetes

• Flexible work arrangements, including part-time work, working outside normal 9–5 business hours, or working remotely
• Welcome back program supporting people returning to work after a long break due to health or family reasons
• Inclusive workplace culture embracing diverse perspectives
• Career growth opportunities