Position overview: We are seeking a Principal AI Architect to lead AI strategy and innovation initiatives within DataArt’s Google Cloud Partnership. This role combines strategic consulting, hands-on AI leadership, and partnership development across AI/ML, analytics, and cloud transformation domains. As a senior member of the partnership business unit, you will collaborate with executive stakeholders, guide the development of AI capabilities, and drive the adoption of Google Cloud technologies across clients’ AI and digital transformation programs. You will also support go-to-market strategies and contribute to shaping DataArt’s AI and GCP offerings.
- Responsibilities: Serve as the primary AI architect and trusted technical advisor to clients, understanding their business challenges and identifying opportunities for AI-driven innovation.
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Lead pre-sales and client technical engagements as a GCP expert, shaping transformation roadmaps, reference architectures, scope estimations, and value propositions.
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Run workshops and working sessions with client teams, engineering leads, and business stakeholders.
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Ensure customers' AI projects align with business objectives, maintain technical excellence, and comply with ethical AI and data privacy principles.
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Lead change management efforts to support clients transitioning to AI-enabled and agent-driven operating models.
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Provide expert guidance on AI technologies, frameworks, MLOps, and architectures suitable for complex enterprise environments.
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Contribute to DataArt’s go-to-market and solution development for Google Cloud, with focus areas including Generative AI, Vertex AI, analytics, data platforms, and application modernization.
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Collaborate with industry and enterprise account teams to promote GCP capabilities, support deal structuring, and accelerate cloud adoption.
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Mentor and support AI delivery teams, contributing to internal training programs, certifications, and capability growth.
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Guide the evolution toward AI-augmented software delivery, integrating AI agents into development workflows and modernizing delivery practices.
- Requirements: Proven track record leading technical pre-sales, opportunity qualification, solution pitching, RFP/RFI responses, and effort estimation for enterprise clients.
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7+ years of experience in AI solution architecture, cloud transformation, or technical leadership, ideally with team leadership responsibilities.
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Proven expertise in AI/ML technologies and architectural best practices within enterprise environments.
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Experience developing, designing, and delivering AI and data strategies on Google Cloud Platform (GCP), leveraging Gemini Enterprise Agent Platform (formerly Vertex AI), BigQuery, Spanner, Knowledge Graphs, Semantic layers, Dataflow, Apache Beam, or Databricks.
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Demonstrated ability to translate ideas into working prototypes through rapid, hands-on execution using vibe coding, AI Studio, Antigravity, and related tools such as ADK.
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Experience delivering enterprise programs around Gemini Enterprise adoption and LLM integration.
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Strong track record of driving AI initiatives from early pre-sales ideation through to production implementation.
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Experience working directly with C-level executives and translating business needs into AI-driven architectures and solutions.
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Hands-on collaboration experience with data scientists, ML engineers, and software development teams.
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Solid understanding of ethical AI, data privacy, and compliance frameworks.
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Excellent communication, pre-sales presentation, multi-stakeholder management, and leadership skills.
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An advanced degree in Computer Science, AI, Data Science, or a related field is preferred.
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Deep knowledge of Google Cloud technologies; GCP certification (e.g., GCP Professional Cloud Architect or Professional Machine Learning Engineer) or readiness to achieve certification quickly.
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Experience designing AI training and enablement programs that drive measurable adoption.
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Familiarity with AI governance frameworks and responsible AI policies.
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Understanding of emerging AI-native SDLC models and agentic delivery methodologies.
- Nice to have: Familiarity with other major cloud AI platforms (AWS, Azure) and enterprise cloud data platforms (Databricks and Snowflake).
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Exposure to AI-augmented or agent-orchestrated software delivery and its impact on team structures.
