Senior Deployment Strategist – Cloud & AI

This is a fully remote position, open to applicants in Canada, +1 more country.

📋 Description

• Collaborate with executive sponsors to convert vague directives into tangible, time-limited projects supported by solid business cases.

• Direct technical discovery and conduct architecture evaluations.

• Highlight integration challenges, infrastructure limitations, change-control realities, and technical trade-offs.

• Build technical credibility with customer engineering teams and define engagements focused on deployable, verifiable results.

• Organize multi-phase cloud and AI optimization deployment roadmaps.

• Work in tandem with customer engineers on infrastructure and AI enhancement.

• Take ownership of architectural decisions, technical issue resolution, guardrails, policy frameworks, and integration into client workflows and change protocols.

• Manage ticketing, change templates, approval processes, security, and compliance requirements.

• Diagnose and adapt to technical or organizational limitations while ensuring stakeholder alignment.

• Establish adoption and impact metrics prior to deployment and take responsibility for measurable results.

• Convert business goals into technical execution and technical limitations into business choices.

• Design proof-of-concept scope, success criteria, and pathways to production.

• Advocate for expansion alongside the account team.

• Identify further optimization opportunities within client environments.

• Transform field insights into reusable playbooks.

• Offer technically specific product feedback to influence the development roadmap.

• Collaborate effectively and independently while supporting practice growth.

⛳️ Requirements

• Over 10 years of comprehensive technical infrastructure, engineering, architecture, or technical delivery experience.

• Significant public-cloud experience and profound expertise in at least one of AWS, Azure, or GCP.

• A solid foundation in software engineering with substantial responsibility for production systems.

• Experience in enterprise-scale architecture, covering areas such as multi-account or multi-region setups, high availability, horizontally scalable systems, networking, security, governance, and compliance.

• Strong technical problem-solving abilities, including reasoning from first principles and justifying architectural choices with senior engineers.

• Proficiency in infrastructure economics and technical expenditure drivers.

• Deep production experience in at least two of GPU and accelerator infrastructure, inference optimization and economics, or agentic/LLM architectures.

• Familiarity with enterprise AI platforms like Bedrock, Azure OpenAI, Vertex AI, and relevant neocloud offerings.

• Proven application of AI in daily engineering, architecture, and consulting tasks.

• Demonstrated experience working directly with external customers in consulting, professional services, solutions architecture, forward-deployed engineering, deployment strategy, or similar client-facing technical delivery roles.

• Ability to engage with CTO-level stakeholders and customer engineers.

• Experience in owning technical outcomes with external clients.

• Background in operating production systems.

• High sense of ownership, collaboration, and comfort with ambiguity.

• Experience with production Kubernetes is advantageous but not mandatory.

• Preferred: formal FinOps practice experience or certifications, leadership in cloud/platform/AI/FinOps practice, experience in regulated industries, datacenter/colocation/hybrid estate experience, Terraform and policy-as-code familiarity, and skills in public speaking or technical writing.

🏝️ Benefits

• Fully remote work opportunities across the Americas.

• 10–20% travel to client locations.

• Collaborate with a globally distributed team of technologists.

• Direct access to product teams; field insights help shape the product roadmap.