Senior Deployment Strategist - Cloud & AI

📋 Job Overview

Most enterprises don't have a cloud and AI cost problem. They have a deployment problem. They may already know their GPU fleet is oversubscribed, their inference bill is compounding, or parts of their estate are running inefficiently. What they often lack is someone who can walk into a risk-averse engineering organization, identify the highest-leverage change, solve the technical problem deeply enough to earn credibility, and get the change into production. That is this job. Not analysis - optimization deployment.

🏢 About Virtasant

We are hiring Sr Deployment Strategists because the constraint is no longer simply finding inefficiency. It is landing the fix inside a real organization, with real approval gates, tribal knowledge, and engineers who may not have asked for a vendor's opinion. You will own that journey from the first workshop through production change and measurable business impact.

🎯 The Role

Partner with executive sponsors - CTO, VP Infrastructure, VP Engineering, Head of AI Platform - to turn ambiguous mandates into concrete, time-boxed deployments with a defensible business case. Lead technical discovery and architecture review. Surface integration complexity, infrastructure constraints, change-control realities and the technical tradeoffs that determine whether an engagement is feasible.

✅ Key Responsibilities

• Partner with executive sponsors to turn ambiguous mandates into concrete, time-boxed deployments with a defensible business case.
• Lead technical discovery and architecture review, identifying integration complexity and infrastructure constraints.
• Establish technical credibility quickly with customer engineering teams and challenge assumptions constructively.
• Scope engagements around outcomes that can be deployed and verified.
• Sequence multi-phase cloud and AI optimization deployment roadmaps against the client's real readiness.
• Work alongside customer engineers on infrastructure and AI optimization, owning architecture decisions and technical problem solving.
• Get changes through the client's existing workflows - ticketing, change templates, approval routing, security and compliance gates.
• Define adoption and impact metrics before deployment and hold yourself accountable to them.
• Own the executive narrative from kickoff through handoff, translating business outcomes into technical implementation.
• Design POC scope, success criteria and the graduation path into production.
• Turn field learnings into reusable playbooks so the next deployment starts further ahead.
• Push product gaps, integration friction and recurring client pain back into Helias with enough technical specificity to influence the roadmap.

📌 Required Qualifications

• 10+ years of overall technical infrastructure, engineering, architecture or technical delivery experience, with meaningful public-cloud experience and deep expertise in at least one of AWS, Azure or GCP.
• A genuine software engineering foundation and meaningful responsibility for production systems.
• Enterprise-scale architecture experience across areas such as multi-account or multi-region environments, high availability, horizontally scalable systems, networking, security, governance and compliance.
• Strong technical problem solving: able to reason from first principles, go deep on architectural tradeoffs and failure modes, and defend technical decisions with senior engineers.
• Fluency in infrastructure economics and the technical drivers of spend - instance and cluster sizing, scheduling, storage, data transfer and architectural rework - with judgment about which changes are worth making.
• Candidates must demonstrate strong production depth in at least two of the following three areas: GPU and accelerator infrastructure, inference optimization and economics, or agentic / LLM architectures.
• Working knowledge of the enterprise AI platform landscape - such as Bedrock, Azure OpenAI, Vertex AI and relevant neocloud offerings - and the tradeoffs between them.
• Demonstrated use of AI in your own daily engineering, architecture and consulting work.
• Demonstrated experience working directly with external customers in consulting, professional services, solutions architecture, forward-deployed engineering, deployment strategy, or a comparable client-facing technical delivery role.
• Evidence of owning technical outcomes with a customer or counterparty who had no obligation to accept your recommendation.
• Ability to move between CTO-level conversations and deep technical discussions with customer engineers, communicating clearly and concisely at both levels.
• Demonstrated use of AI in your own daily engineering, architecture and consulting process, not only experience delivering AI products for others.
• Operator instinct - you have built, owned or run production systems and understand what execution actually costs.
• High ownership, collaboration and comfort with ambiguity.

⭐ Desirable Experience

• Deep operational Kubernetes specialization.
• Formal FinOps practice experience or certifications.
• Experience founding or running a cloud, platform, AI or FinOps practice.
• Depth in a regulated vertical such as financial services, healthcare and life sciences, energy, manufacturing or telecom.
• Datacenter, colocation or hybrid-estate experience alongside cloud.
• Terraform and policy-as-code.
• Public speaking or writing about cloud, AI infrastructure, Kubernetes, optimization or related technical topics.

🎁 Benefits

Fully remote across the Americas, with 10–20% client travel. Deployment is the product. Our strategists and FDEs are not a services wrapper on a platform - they are the reason the platform produces results. No selling software. You are accountable for whether the deployment landed and produced a verified outcome. Scale behind you. Work with a globally distributed network of technologists and a platform built around context-aware optimization. Direct line to product. What you find in the field influences what we build.

🛂 Visa & Eligibility

Remote, Americas (US, Canada, Latin America) eligibility.