DATAECONOMY Inc.
Job Description
AWS GenAI Architect Onshore - Boston
Full-time
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.
Full-time
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.