Senior Director, Solution Engineering, Google Cloud

Publicis Groupe•Seattle, WA

4d•$150,000 - $230,000

About The Position

We are seeking a high-impact GCP Solutions Technical Leader to join our North America Google Business Unit. In this pivotal role, you will architect innovative AI/ML solutions aligned with Google Cloud's product roadmap, consult with clients, and lead high-stakes pre-sales activities. You will guide prospective and current clients in harnessing the power of Google Cloud, translating complex technical features into tangible business outcomes while resolving critical roadblocks. This role is also an internal force-multiplier: you will work across engineering leaders and delivery teams to surface “what's working,” capture reusable implementation know-how, and convert it into repeatable go-to-market assets, demos, and rapid POCs—often in partnership with Google teams. You will bring pattern-thinking across multiple industry verticals (e.g., Financial Services and Retail) and apply those learnings to accelerate solutioning across other industries.

Requirements

Professional Experience: 10-12+ years of experience in solution architecture with a career-defining focus on AI/ML and GCP cloud technologies.
Technical Depth: Deep expertise in Big Data, PaaS, and IaaS technologies, specifically within the Google Cloud Platform ecosystem.
AI/ML Specialization: Data-centric experience with a proven track record of architecting and delivering AI/ML-based solutions.
Hands-on Builder: Demonstrated ability to rapidly prototype using modern AI-assisted development tools, producing working demos and production-minded reference implementations.
Cross-Industry Pattern Thinking: Experience delivering solutions across multiple industry verticals (e.g., Financial Services and Retail) with the ability to abstract common patterns and apply them to other domains.
Customer-Facing Leadership: Prior leadership experience as a Cloud Architect or similar role within professional services or systems engineering.
Stakeholder Management: Confident in delivering clear, persuasive technical pitches and solutioning for both technical SMEs and executive-level audiences. Proven ability to align multiple engineering leaders and teams around reusable solution patterns that strengthen go-to-market execution.

Nice To Haves

Advanced Certifications: Current Professional Google Cloud certifications, specifically Cloud Architect, Data Engineer, and Machine Learning Specialty.
Strategic Ecosystem Connections: A robust professional network and established relationships with Google Partner Teams, particularly Partner and Customer Engineering groups.
Complex Platform Integrations: Proven technical exposure to orchestrating integrations between GCP and third-party enterprise platforms, including Salesforce, Oracle, and VMware environments.
Innovation & Specialized Knowledge: Demonstrated experience in building and leading innovation-led technical teams using agile frameworks, including establishing “POC-to-offering” pathways (reference implementations, demo assets, accelerators).
Cross-Platform Synergy: A sophisticated understanding of the Google Marketing Platform (GMP) and Google Ads ecosystem to drive unified data and marketing solutions.
Technical Governance: Deep comfort collaborating with senior technical stakeholders on complex topics such as Security, Data Privacy, and Information Management.
Thought Leadership & Public Presence: Experience presenting in GCP forums (e.g., Google Cloud Next and partner events), with credibility as a practitioner who can translate real implementations into clear points of view.

Responsibilities

Architectural Engineering & Design: Engineer end-to-end, cloud-native architectures on GCP by orchestrating IaaS, PaaS, and Big Data services to support scalable, distributed systems. This includes architecting production-grade AI/ML pipelines using Vertex AI, Gemini, and Agentic AI frameworks while adhering to enterprise pillars of security, cost-optimization, and high-availability.
Hands-on Delivery & Prototyping: Actively collaborate with project teams to demonstrate, experiment with, and prototype GCP product integrations and practical use cases within customer and partner environments. You will be personally hands-on, working with small dev teams to rapidly build POCs that prove capability and de-risk client decisions. You will use modern AI developer tools extensively to accelerate prototyping, iteration speed, and quality.
Customer Advisory: Conduct discovery sessions to deeply understand client requirements and provide expert guidance on AI/ML best practices and implementation strategies, informed by real implementations across industries.
Pre-Sales Leadership: Drive pre-sales efforts by creating compelling technical proposals, conducting technical deep-dives, and collaborating with sales teams to develop winning strategies. Lead early-stage solution definition and shape the “first version” of a client solution alongside engineering and sales leadership.
Technical Evangelism: Evangelize and educate delivery teams on “Why Google Cloud and How?” while staying at the forefront of emerging AI/ML technologies. Curate and share field learnings across teams so successful patterns become repeatable offerings.
Strategic Road-mapping: Recommend integration strategies, enterprise architectures, and the application infrastructure required to implement complete solutions using GCP best practices. Maintain a current view of GCP services and trends, and translate them into practical solution plays and accelerators.
Reusable Solution Assets & Demo Repository: Build and maintain a personal and team-accessible repository of practical examples—reference architectures, code samples, POCs, and demos—that can be reused across pursuits. Be able to point to published examples of solutions you've built (e.g., code repositories, demo applications, technical write-ups) to establish credibility and accelerate client conversations.
Engineering Leader Co-Partner: Serve as a trusted co-partner to engineering leaders—helping them evolve solutions in the earliest stages, stress-test feasibility, sharpen the technical narrative, and show up with strong demos and relevant industry examples when it matters.
Strategic Ecosystem Alignment: Cultivate and deepen technical relationships with Google Partner and Customer Engineering teams to manage product briefings and coordinate specialized resources for complex solutioning.
Joint Innovation & Feedback Loops: Collaborate with Google product management and engineering teams to stay ahead of industry trends and provide field feedback to refine Publicis Sapient's GCP solutions and accelerators.