Vendor Solutions Consultant, AI and Engineering Solutions
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Boulder, CO, USA; Chicago, IL, USA; Kirkland, WA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in management consulting or a client-facing role.
Preferred qualifications:
- Experience in translating AI advancements and intelligent automation capabilities into engineering vendor solutions and commercial models (e.g., pay-per-use (PPU), managed services).
- Experience working with engineering services and AI landscape, with enterprise technology services workflows, including FDE, data acquisition, connector builds, threat intel, security, and red-teaming.
- Experience with multi vendor operations management for scaled operations, vendor relationship management, and engaging with executive vendor account leaders.
- Ability to communicate and influence cross-functionally and at the executive level.
- Ability to build strong relationships with clients and act as a trusted advisor and partner.
- Excellent organizational and project management skills.
About the job
In this role, you will support the implementation of the Vendor Management Office (VMO) roadmap. This position demands a minimum of 10 years in transformation consulting, alongside comprehensive knowledge of Core Engineering Services, the AI Data operations sector and the Enterprise Technology Services domain, encompassing new engineering and AI worktypes like full disk encryption (FDE), data acquisition, threat intel, and security. Tasked with managing vendor strategy and procurement for AI and Cloud Engineering, you will create efficient, scalable operating structures while overseeing compliance and operational safety.
You will partner strategically with Google Cloud stakeholders to execute the VMO goals and will engineer cost-effective, scalable operational models while mitigating compliance risks. You will serve as a subject matter lead for the extended workforce and vendor ecosystem. You will oversee critical functions such as rate card evaluation, vendor selection, and global location strategy.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $140000 - $205000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage or work within enterprise technology Services workflows, including FDE, data acquisition, connector builds, threat intel, security, and other related engineering and AI worktypes.
- Execute vendor strategy and contracting specifically for Cloud Engineering and AI solutions requirements.
- Develop scalable, cost-optimal operating models and drive supplier quality through structured governance and measurement.
- Deliver global initiatives to transform services while monitoring operational and compliance risks.
- Embed AI as a core component of solutions, leveraging learning and automation for transformative outcomes.

