AWS GenAI Architect

AWS GenAI Architect | Onshore – Boston

Job Summary:

We are seeking a highly skilled and innovative GenAI Architect to lead the design, implementation, and governance of next-generation AI solutions leveraging AWS-native services. The ideal candidate will have deep experience. in AWS GenAI services, security frameworks, service enablement patterns, and infrastructure automation using Terraform. This role will be instrumental in architecting scalable, secure, and responsible AI systems for enterprise-grade applications.

Roles & Responsibilities:

Architecture & Design

·         Architect and design Generative AI solutions using Amazon Bedrock, SageMaker, Amazon Q, and Agents for Amazon Bedrock.

·         Define multi-tenant and scalable architectures that ensure data security, isolation, and performance.

·         Develop architecture blueprints and high-level design documents for GenAI workloads.

Security & Governance

·         Define and implement security guardrails across the GenAI ecosystem (IAM, SCPs, encryption, network boundaries).

·         Ensure responsible AI practices, including data governance, privacy, bias mitigation, and human-in-the-loop mechanisms.

·         Establish policies for prompt management, model access control, and API usage monitoring.

Service Enablement & Integration

·         Enable and onboard AI capabilities as reusable services and APIs for enterprise-wide adoption.

·         Integrate GenAI services with backend systems, enterprise data lakes, DynamoDB, and external APIs.

·         Orchestrate AI workflows using Amazon Q and agents for complex enterprise tasks and reasoning.

Automation & Infrastructure

·         Implement and manage GenAI infrastructure using Terraform, with emphasis on reusable modules, compliance checks, and CI/CD.

·         Collaborate with Platform/DevOps teams to build standardized environments for rapid experimentation and deployment.

Innovation & Evangelism

·         Act as a thought leader on GenAI, sharing emerging trends and best practices across teams and leadership.

·         Conduct POCs and technical workshops to drive AI adoption and maturity within the organization.

·         Contribute to internal knowledge repositories and reusable solution accelerators.

Preferred Qualifications:

·         AWS Certified Machine Learning – Specialty or AWS Solutions Architect certifications.

·         Experience working in regulated industries (e.g., finance, healthcare).

·         Exposure to Open Source LLMs (LLaMA, Mistral, Falcon) and foundation model fine-tuning practices.

·         Familiarity with MLOps pipelines, including model lifecycle management and versioning.

Requirements

         12 to 15+ years in solution architecture or AI/ML engineering, with 4+ years in GenAI-related projects.

·         Strong expertise in Amazon Bedrock, SageMaker (incl. JumpStart, Pipelines, Model Registry), Amazon Q, and Agents for Bedrock.

·         Deep understanding of AWS IAM, VPC, KMS, and security best practices for GenAI workloads.
Hands-on experience with DynamoDB, including data modeling, performance tuning, and integration.

·         Solid skills in Terraform (preferably Terraform Enterprise) for infrastructure provisioning and automation.

·         Understanding of GenAI concepts including RAG (Retrieval Augmented Generation), prompt engineering, vector databases, model evaluation, and fine-tuning.

·         Proficient in Python and experience with AWS SDKs, LangChain, or similar frameworks is a plus.

·         Excellent communication and stakeholder management skills across business and engineering teams.