Senior Deployment Strategist - Cloud & AI

Senior Deployment Strategist - Cloud & AI

Location: Remote, Americas (US, Canada, Latin America) | Travel: 10–20% to client sites
Why this role exists

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.

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.
What you'll own
Scope

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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.

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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.

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Establish technical credibility quickly with customer engineering teams, challenge assumptions constructively, and say no to work that will not land.

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Scope engagements around outcomes that can be deployed and verified, not analysis or recommendations that stop at a slide deck.

Deploy

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Sequence multi-phase cloud and AI optimization deployment roadmaps against the client's real readiness.

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Work alongside customer engineers on infrastructure and AI optimization. Own architecture decisions, technical problem solving, guardrails and policy layers, and integration into the client's pipelines and change process; customer engineers may own portions of deep implementation.

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Get changes through the client's existing workflows - ticketing, change templates, approval routing, security and compliance gates - rather than working around them.

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Diagnose and adjust when technical or organizational constraints emerge mid-flight, keeping sponsors and engineering teams aligned on the outcome.

Own the outcome

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Define adoption and impact metrics before deployment and hold yourself accountable to them.

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Own the executive narrative from kickoff through handoff, translating business outcomes into technical implementation and technical constraints back into business decisions.

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Design POC scope, success criteria and the graduation path into production, and own the case for expansion alongside the account team.

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Identify additional optimization opportunities as you learn the client's environment.

Make the organization better

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Turn field learnings into reusable playbooks so the next deployment starts further ahead.

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Push product gaps, integration friction and recurring client pain back into Helias with enough technical specificity to influence the roadmap.

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Operate collaboratively and independently: support the expansion of the team, remove obstacles without waiting for hand-holding, and consistently work toward the outcome.

What you'll need
Deep technical problem-solving and cloud infrastructure credibility - non-negotiable

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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.

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A genuine software engineering foundation and meaningful responsibility for production systems. Strong candidates may have progressed from Software Engineer to Technical Lead / Staff / Principal Engineer and into bro