Lead AI Engineer - AWS Platform

Job Description:

We are modernizing our data and analytics ecosystem by embedding AI and Generative AI across core insurance platforms (Policy, Claims, Billing, and Enterprise systems).

We are hiring a Lead AI Engineer to build and scale production-grade AI solutions on AWS. This role is hands-on and focused on delivering real systems, while helping shape the foundation of our emerging AI platform.

This is not a pure research or modeling role. It is an engineering role focused on building, deploying, and operating AI systems in a regulated enterprise environment.

Build AI Systems (Core Responsibility)

• 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 that automate their training, validation, monitoring, and retraining

• Develop APIs and services to operationalize AI capabilities across the organization

Develop Data + AI Pipelines

• Build ingestion for multimodal content and transformation pipelines for structured and unstructured data

• Integrate AI workflows with enterprise systems (policy, claims, billing, etc.)

• Ensure data quality, traceability, reliability, and governance in all AI pipelines

Operationalize Models (MLOps)

• Implement CI/CD for AI/ML workflows

• Deploy, monitor, and maintain models in production

• Manage model versioning, performance monitoring, and retraining processes

Build on AWS

• Develop solutions using: Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services

• Contribute to evolving use of AWS Bedrock

Apply Responsible AI Practices

• Implement guardrails for LLM-based systems (grounding, validation, safety)

• Ensure secure handling of sensitive data (PII, financial, etc.)

• Build systems aligned with enterprise governance and compliance standards

Lead by Doing

• Provide technical guidance and mentorship to engineers

• Contribute to engineering standards and reusable patterns

• Partner with architects and business teams to deliver high-impact use cases

Qualifications:

Required

• 10+ years in software, data engineering, 5 years AI/ML engineering

• 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 (CI/CD, monitoring, versioning)

Preferred

• Experience with vector databases (Pinecone, Weaviate, etc.)

• Experience in regulated industries (insurance, finance, healthcare)

• Exposure to microservices and containerized environments (Docker, Kubernetes)