What are the responsibilities and job description for the Agentic and GEN AI Architects/Engineers position at Jobs via Dice?
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We just got a new bulk and bid from our client with 4 openings for Agentic/GEN AI Developers and Architects. Candidates don’t need to have architecture experience or all the must haves, any solid Agentic/GEN AI or any AI/LLM experience is fine for submittal.
Top Requirements:
4 years of Systems Architecture experience, with hands‑on enterprise architecture design (not advisory-only).
GenAI architecture experience, including agentic workflows, LLM reasoning, and AI‑enabled governance automation.
Architecture-as-Code (AaC) using Structurizr, C4 modeling, scripts, generators, and CI/CD-integrated model validation.
Azure and Google Cloud Platform cloud architecture, onboarding patterns, landing zones, and SDLC/developer platform integration.
Strong automation background: CI/CD integration, governance automation, scripting, and infrastructure automation.
Job Summary:
This contingent Systems Architect role supports moderately complex architecture initiatives and contributes to enterprise‑wide planning. As a GenAI Architecture Consultant, the resource will design AI‑augmented architecture patterns, build Architecture-as-Code automation, enforce DCMS governance, lead Azure/Google Cloud Platform onboarding architectures, evolve enterprise patterns (Archetype 2.0), and support next‑gen Permit‑to‑Build automation leveraging LLM reasoning.
The role is essential to advancing CTO Architecture OKRs, scaling AI‑first governance, and improving architectural consistency, automation, and safety across the enterprise.
Day-to-Day Responsibilities:
Develop AI-augmented architecture patterns and integrate AI into the SDLC.
Prototype agentic workflow architectures and GenAI-enabled patterns.
Build hands-on POCs improving observability, governance enforcement, and system intelligence.
Create scripts, generators, model pipelines, and CI/CD-integrated architecture validation.
Produce high-quality architecture deliverables and enforce DCMS governance.
Validate architecture submissions, remediate design gaps, and ensure consistency across teams.
Lead Azure & Google Cloud Platform onboarding architecture, including PAA onboarding, dev environment patterns, SDLC tooling, and reusable accelerators.
Evolve enterprise reference architectures and Archetype 2.0, including code templates and prototype applications.
Co-design next-gen Permit-to-Build automation, integrating LLM reasoning, metadata ingestion, automated validations, and model-driven tooling.
Collaborate with developers, platform teams, security, risk partners, and CTO Architecture leadership.
Communicate complex AI‑enabled architectural concepts clearly to both technical and non-technical audiences.
We just got a new bulk and bid from our client with 4 openings for Agentic/GEN AI Developers and Architects. Candidates don’t need to have architecture experience or all the must haves, any solid Agentic/GEN AI or any AI/LLM experience is fine for submittal.
Top Requirements:
4 years of Systems Architecture experience, with hands‑on enterprise architecture design (not advisory-only).
GenAI architecture experience, including agentic workflows, LLM reasoning, and AI‑enabled governance automation.
Architecture-as-Code (AaC) using Structurizr, C4 modeling, scripts, generators, and CI/CD-integrated model validation.
Azure and Google Cloud Platform cloud architecture, onboarding patterns, landing zones, and SDLC/developer platform integration.
Strong automation background: CI/CD integration, governance automation, scripting, and infrastructure automation.
Job Summary:
This contingent Systems Architect role supports moderately complex architecture initiatives and contributes to enterprise‑wide planning. As a GenAI Architecture Consultant, the resource will design AI‑augmented architecture patterns, build Architecture-as-Code automation, enforce DCMS governance, lead Azure/Google Cloud Platform onboarding architectures, evolve enterprise patterns (Archetype 2.0), and support next‑gen Permit‑to‑Build automation leveraging LLM reasoning.
The role is essential to advancing CTO Architecture OKRs, scaling AI‑first governance, and improving architectural consistency, automation, and safety across the enterprise.
Day-to-Day Responsibilities:
Develop AI-augmented architecture patterns and integrate AI into the SDLC.
Prototype agentic workflow architectures and GenAI-enabled patterns.
Build hands-on POCs improving observability, governance enforcement, and system intelligence.
Create scripts, generators, model pipelines, and CI/CD-integrated architecture validation.
Produce high-quality architecture deliverables and enforce DCMS governance.
Validate architecture submissions, remediate design gaps, and ensure consistency across teams.
Lead Azure & Google Cloud Platform onboarding architecture, including PAA onboarding, dev environment patterns, SDLC tooling, and reusable accelerators.
Evolve enterprise reference architectures and Archetype 2.0, including code templates and prototype applications.
Co-design next-gen Permit-to-Build automation, integrating LLM reasoning, metadata ingestion, automated validations, and model-driven tooling.
Collaborate with developers, platform teams, security, risk partners, and CTO Architecture leadership.
Communicate complex AI‑enabled architectural concepts clearly to both technical and non-technical audiences.