AI Architect with Google Cloud PlatformVertexAI
Remote • Posted 2 days ago • Updated 2 hours agoFull Time
Remote
Depends on Experience
Marici Solutions
Fitment
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Job Details
Skills
- AI Architect with GCPVertexAI
Summary
AI Architect with Google Cloud Platform Vertex AI Remote
Full Time
Experience / Skills
Full Time
Experience / Skills
- 10 12 years in AI/ML, Cloud, platform engineering, or enterprise architecture roles
- 3+ years of hands-on experience with Google Cloud Platform Vertex AI, including real work with components such as Agentspace, Agent Builder, Vector Search (Matching Engine) and/or Search & Conversation
- 1-year of hands-on experience with Agent Development, Agentspace, Agent Builder, Search & Conversation; able to describe at least one actual solution built on Vertex AI
- Experience designing enterprise-grade AI, GenAI or Agentic systems including aspect of Agent Ops and Ob Behalf of Workflows; Exposure to multi-cloud AI environments (Azure OpenAI, Copilot Studio, OpenAI API)
- 2+ years of experience building Generative AI applications, such as AI assistants, retrieval-based systems, or LLM-powered workflows. The candidate should clearly explain what they built and what their role was
- 5+ years of strong Python development experience, specifically building backend services, APIs, Microservices, or automation components used in production environments
- Practical integration experience with at least one enterprise platform (SAP, Salesforce, or ServiceNow), with the ability to describe a real integration scenario they worked on
- 3+ years of Cloud deployment experience, preferably using Google Cloud Platform services like Cloud Run, Cloud Functions, or Kubernetes for deploying and maintaining cloud-native applications
- 1 year of experience operationalizing AI systems, managing prompts or models, handling errors/failures, monitoring performance/improving system reliability; Exposure to LLMOps / similar processes
- Basic working knowledge of enterprise security and data protection, including responsible handling of sensitive data, access control, and safe use of AI systems in an enterprise environment
- Bachelor s or Master s degree in Computer Science/ CIS, IT/ Data Science, Engineering, or a related technical discipline
- Strong communication skills, with the ability to explain past projects clearly, walk through their contributions, and provide understandable examples of their AI and cloud experience
As a Principal AI Architect specializing in Google Cloud Platform Vertex AI and Agentic AI, you will guide the architecture, strategy, and delivery of enterprise-grade AI platforms. Work closely with engineering, platform, and business teams to shape the AI roadmap, design scalable agentic systems, and ensure responsible adoption of Generative AI across the organization. This is an architecture role with direct responsibility for how AI capabilities are designed, integrated, and deployed across the enterprise. You will:
- The Google Cloud Platform Vertex AI + Agentspace architecture
- Standards for agent development patterns, grounding, and memory
- Integration of agents with SAP/Salesforce/ServiceNow
- A2A (Agent-to-Agent) coordination and orchestration design
- Context Engineering patterns for reliable grounding
- Approaches for testing, observability, safety, and control in GenAI systems
- Enterprise governance, LLMOps, AgentOps, and lifecycle management
Primary Responsibilities
- Architect Scalable Vertex AI & Agentspace Solutions Design and deliver AI architectures built on Google Cloud Platform Vertex AI and Agentspace, covering agent workflows, retrieval pipelines, vector search, grounding logic, tool integrations, and multi-agent (A2A) coordination; Ensure the platform is secure, resilient, and built for scale
- Platform Strategy & Technical Direction Provide guidance on architecture patterns, technology choices, and platform evolution; Help teams understand trade-offs, make decisions that align with long-term business outcomes
- RAG Systems & Context Engineering Lead the design of retrieval pipelines and context strategies that produce reliable, high-quality responses; Define how data is chunked, embedded, searched, and assembled into grounded context windows for agents
- Agentic AI Frameworks & A2A Patterns Define patterns for building and coordinating agents across Agentspace, LangGraph, DSPy, or similar frameworks; Establish approaches for delegation, task planning, error recovery, and safe inter-agent communication
- Tooling Integration & MCP-Style Interfaces Architect how agents call tools and external systems; Define tool schemas, safety constraints, validation rules, and execution boundaries across SAP, Salesforce, ServiceNow, and enterprise APIs
- LLMOps & AgentOps Set up operational foundations for prompts, models, and agents including CI/CD pipelines, monitoring dashboards, version control, error tracking, and cost governance; Implement guardrails that reduce hallucinations and prevent unsafe or unintended behavior
- Design Authority & Governance Lead architecture reviews, define reference architectures, and establish reusable patterns. Ensure every GenAI initiative adheres to security, data governance, and platform standards
- Cross-Functional Collaboration Work closely with engineering, data, product, and business teams to convert use cases into practical, production-ready architecture. Break down complexity so teams can execute confidently
- Documentation & Standards Create and maintain playbooks, best practices, design guides, and reference implementations that help distributed teams build consistently
- Monitoring, Testing & Observability Establish testing frameworks for retrieval quality, agent behavior, grounding accuracy, and safety signals; Guide development of AgentOps dashboards that track performance, tool failures, latency, drift, and system health
Secondary Responsibilities
- Platform Research & Innovation Stay current with advancements across Vertex AI, Agentspace, Model Garden, and broader agentic patterns. Bring forward ideas worth evaluating and scaling
- Proof of Concepts Lead/sponsor PoCs to validate feasibility, performance business value before full-scale adoption
- Ecosystem Awareness Maintain familiarity with Azure OpenAI, Copilot Studio, AI Studio, Cognitive Search, and other cloud AI platforms to support multi-cloud strategy
- Business Alignment Engage with product and business leaders to identify impactful use cases, help shape roadmaps, and clarify expected outcomes
- Mentorship & Skill Building Support engineers through coaching on RAG tuning, prompt refinement, agent patterns, testing techniques, and responsible AI practices
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91138214
- Position Id: 8868207
- Posted 2 days ago
Company Info
About Marici Solutions
MARICI Solutions is a global business consulting organization, where inspired & visionary people with a shared passion for innovation come together to make a difference. We take a holistic approach from various perspectives to deliver measurable results along the entire value chain. We work closely with our clients and provide distinct advantages to sustainably transform their business processes, which eventually grow their businesses.
Driven by the passion of offering state of the art, customized and high-quality information technology services, our experts from Germany & India came together in 2017 and formed MARICI Solutions GmbH. The company is registered in Germany & India and well funded for long term sustenance. The team at MARCI comprises of experts from various industry sectors who have more than a decade of diverse & international consulting experience. MARICI is expanding its business across multiple continents and has secured various projects from some of the eminent market giants.
We believe that Excellence, Collaboration, Commitment and Innovation are foundations for success.
By Collaborating with our stakeholders, we identify opportunities for growth and Innovation. Ongoing innovation results from a combination of strategy, processes, systems, and culture. Through our Commitment to Excellence, we accomplish complex assignments and inspire people to do great things together.
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