Description

You design end-to-end AI architectures covering ingestion, storage, retrieval, reasoning, action, and monitoring.

You will own and evolve reference architectures for Document AI, Conversational AI, and Agentic AI. Specify non-functional requirements, including latency, throughput, privacy, compliance, observability, and cost. Select and justify AWS-native AI/ML services and third-party tools. Govern prompt and version management, enforcing safety policies and managing controls for prompt injection and PII protection. Lead Proofs of Concept to production using AWS-based templates and golden paths.

Responsibilities

• Own and evolve reference architectures for Document AI, Conversational AI, and Agentic AI.
• Specify non-functional requirements, including latency, throughput, privacy, compliance, observability, and cost.
• Select and justify AWS-native AI/ML services and third-party tools.
• Govern prompt and version management, enforcing safety policies and managing controls for prompt injection and PII protection.
• Lead Proofs of Concept to production using AWS-based templates and golden paths.

Required Skills

• 5–10+ years in AI/ML software development.
• 3–5+ years in solution or enterprise architecture.
• Proven experience designing AI systems at enterprise scale on AWS.
• Hands-on experience with AWS Bedrock, SageMaker, Lambda, Kendra, OpenSearch, Redshift, DynamoDB, and S3.
• Expertise in LLMs, vector databases, RAG pipelines, and agentic workflows.
• Strong knowledge of multi-cloud cost and latency tradeoffs.
• Excellent communication, stakeholder engagement, and blueprinting skills.

Preferred Skills

• Insurance industry experience (claims adjudication, underwriting, policy servicing).

Key Skills

Education

Any Gradute