Senior Deployment Strategist - Cloud & AI

Location: Fully remote across the Americas, including the US, Canada, and Latin America; 10–20% travel to client sites.

Company

hirify.global builds and deploys context-aware cloud and AI optimization solutions, with deployment outcomes feeding directly into product development.

What you will do

• Partner with CTOs, infrastructure leaders, engineering executives, and AI platform heads to turn ambiguous mandates into concrete deployments and defensible business cases.
• Lead technical discovery, architecture reviews, integration assessment, and infrastructure tradeoff analysis.
• Sequence and execute multi-phase cloud and AI optimization deployments with customer engineering teams.
• Own architecture decisions, technical problem solving, guardrails, policy layers, and integration with customer pipelines and change-control processes.
• Define adoption and impact metrics, manage the executive narrative, and guide proofs of concept into production and expansion.
• Convert field learnings into reusable playbooks and provide technically specific product feedback.

Requirements

• 10+ years of technical infrastructure, engineering, architecture, or technical delivery experience, including meaningful public-cloud experience and deep expertise in AWS, Azure, or GCP.
• Software engineering foundations with meaningful responsibility for production systems and enterprise-scale architecture.
• Strong understanding of high availability, scalable systems, networking, security, governance, compliance, and infrastructure economics.
• Production AI infrastructure depth in at least two areas: GPU and accelerator infrastructure, inference optimization and economics, or agentic and LLM architectures.
• Experience with external customers in consulting, professional services, solutions architecture, forward-deployed engineering, deployment strategy, or comparable technical delivery roles.
• High ownership, strong collaboration, comfort with ambiguity, and demonstrated use of AI in daily engineering, architecture, or consulting work.

Nice to have

• Deep operational Kubernetes expertise.
• Formal FinOps experience or certifications.
• Experience founding or running a cloud, platform, AI, or FinOps practice.
• Experience in regulated industries, datacenters, colocation, hybrid estates, Terraform, or policy-as-code.
• Public speaking or technical writing on cloud, AI infrastructure, Kubernetes, or optimization.

Culture & Benefits

• Fully remote work across the Americas with 10–20% client travel.
• Deployment is treated as the core product value rather than a services wrapper.
• No software-selling responsibility; accountability centers on whether deployments land and produce verified outcomes.
• Access to a globally distributed network of technologists and a platform focused on context-aware optimization.
• Direct feedback channel from field deployments to the product roadmap.