Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
Numentica

GenAI / Bedrock Architect

Numentica

GenAI / Bedrock Architect responsible for designing secure generative AI solutions on AWS. Leading architecture discussions and enabling customer teams in a remote setting.

Posted 7/7/2026contractRemote • California • 🇺🇸 United StatesSeniorLeadWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and delivering generative AI solutions, with a strong focus on Amazon Bedrock and AWS security fundamentals. Capable of leading technical teams and enabling customer engineering through effective communication and paired delivery.

Highest-signal resume keywords
Generative AI Solution DesignAmazon BedrockAWS Security FundamentalsResponsible AI GovernanceStakeholder Communication

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
RAG PatternsPrompt EngineeringFunction/Tool CallingModel EvaluationData ClassificationPHI/PII HandlingSpec-Driven DevelopmentMCP-Based ToolingMLOpsCI/CD
Soft Skills
Excellent CommunicationStakeholder EngagementTechnical Leadership
Tools & Technologies
Amazon Q BusinessAmazon QuickSightMicrosoft 365ServiceNowJiraDynatraceWiz
Industry Keywords
Regulated EnvironmentsPublic SectorGovernment EnvironmentsAI Reference Architectures

Tech Stack

Tools & technologies
AWSServiceNow

About the role

Key responsibilities & impact
  • Define secure, repeatable AI reference architectures spanning Amazon Bedrock, Amazon Q Business, and Amazon QuickSight as appropriate to the selected use cases.
  • Design generative AI patterns, including foundation model selection criteria, prompt and grounding design, RAG pipelines, agentic workflows, and tool/function calling.
  • Establish the secure AI foundation: identity, role-based access, encryption, logging, data-boundary controls, and audit patterns, working with the Security Architect.
  • Define guardrails, content filtering, prompt-logging policy, human-review patterns, and responsible-AI controls, accounting for data classification and PHI/PII handling.
  • Set the model and retrieval evaluation strategy and quality metrics, including citation and grounding expectations, and oversee iterative tuning.
  • Produce production-readiness gap analysis and a hardening/productionization roadmap.
  • Lead architecture and security review workshops, demos, and enablement office hours with the customer and stakeholders, presenting trade-offs in clear, accessible terms.
  • Enable and upskill the customer's engineering teams through paired design work, including spec-driven development and MCP-based workflows.
  • Provide technical direction to AI Application Engineers and Data/Search Specialists and produce reusable architecture artifacts, reference patterns, and documentation.

Requirements

What you’ll need
  • Strong hands-on experience designing and delivering generative AI solutions, ideally on Amazon Bedrock or comparable foundation-model platforms.
  • Deep understanding of LLM application patterns: RAG, agents, prompt engineering, function/tool calling, grounding/citation, and model evaluation.
  • Solid grounding in the broader AWS stack, including IAM, networking, storage, encryption, logging, and security fundamentals, not just the AI services.
  • Experience defining guardrails, evaluation frameworks, and responsible-AI / governance controls, including data classification and PHI/PII handling.
  • Excellent communication and stakeholder-facing skills; able to lead architecture and security workshops and explain technical concepts to mixed audiences.
  • Proven ability to operate as a technical lead across a small delivery team.
  • Demonstrated experience enabling and upskilling customer engineering teams through paired delivery, not just shipping solutions.
  • Familiarity with spec-driven development workflows and MCP (Model Context Protocol) based tooling.
  • Please provide a list of current AWS certifications
  • Experience delivering AI solutions in regulated or public-sector / government environments.
  • Familiarity with Amazon Q Business and QuickSight, and with enterprise knowledge and BI patterns.
  • Experience integrating with the Microsoft 365 ecosystem (SharePoint, Exchange/Outlook, Teams, OneDrive) and tools such as ServiceNow, Jira, Dynatrace, or Wiz.
  • Background in MLOps, CI/CD, or infrastructure-as-code on AWS.

Benefits

Comp & perks
  • Health insurance
  • Flexible work hours
  • Paid time off