Enterprise Architect - Vertex AI, BigQuery

Role: Enterprise Architect

Location: Las Vegas NV- Hybrid

Duration: Long Term Contract

Rate: Open to Negotiate

 

Description - Enterprise Architect:

·        Definitely Need a hands-on architect with great career progression at the forefront of technology boundaries

·        Has to be clear in their explanations & has to be exposed to many challenges

·        His ability to link a variety of factors into a simple explanation .

·        Has to be very good in event-driven systems, design considerations, performance engineering, and problems caused by schema changes

·        Quick thinker and be able to come up with good answers to one or two very challenging problems - & be able to elaborate multiple perspectives - how different groups may treat a particular challenge (ex:  business mindset vs technology mindset)

·        Excellent communication skills, especially when explaining technical concepts in laymen terms.

Key Responsibilities:

·        Architect and design agentic AI systems tailored for CRM and BPM solutions including requirements to backlog, backlog to build and build to deploy phases of the SDLC

·        Lead the development of autonomous agents capable of reasoning, learning, and collaborating across the test life cycle.

·        Build and optimize AI pipelines using Google Cloud services (Vertex AI, BigQuery, Cloud Functions, etc.).

·        Integrate agents with CI/CD pipelines, test management tools, and developer environments.

·        Ensure seamless deployment and orchestration on AgentSpace, leveraging its capabilities for agent lifecycle management, communication, and scalability.

·        Collaborate with cross-functional teams including QA, DevOps, and product engineering to align AI capabilities with business goals.

·        Define and enforce best practices for agentic AI, including safety, interpretability, and performance monitoring.

·        Stay ahead of emerging trends in LLMs, multi-agent systems, and autonomous software engineering.

Required Qualifications

·        Proven experience as an AI Architect, ML Engineer, or similar role with a focus on agentic or autonomous systems.

·        Strong expertise in Google Cloud Platform and its AI/ML ecosystem.2+ years of experience in building AI/ML solutions, with at least 1+ year focused on generative / Agentic AI. 

·        3+ years experience developing or working with CRM and BPM solutions

·        Familiarity with software testing tools (e.g., Selenium, TestNG, JUnit) and lifecycle processes.

·        Experience deploying and managing agents on AgentSpace or similar platforms.Excellent problem-solving, communication, and leadership skills