Job DescriptionYOU AREAs a Principal AI Infrastructure Architect, you are the firm's most senior technical authority on compute infrastructure for large-scale AI and machine learning systems, bringing extensive experience as a lead and senior architect along with command over a broad landscape of technological options and the latest innovations that can be introduced into a solution. You have a proven track record of successfully designing and deploying large-scale infrastructure on which significant AI/ML solutions operate in production and demonstrably deliver business value - not just systems that perform, but systems that move the needle for the organizations they serve. You weigh and rationalize multipleviablearchitectures acrosscompute, networking, storage, orchestration, and model serving, making authoritative decisions tailored to each client's situation, standards, and strategicobjectives, and you set the technical direction that senior and lead architects build upon. As a recognized expert across at least onehyperscalercloud - and conversant across several - you bring deep, current knowledge of AI/ML services, accelerators, interconnects, and cost levers, and you continuously scan the horizon to identify promising emerging technologies and judge where and when they belong in a real solution. You are well known to our infrastructure partners and partnering organizations,maintainingstrong relationships that give the firmearly access, influence, and insight, and you represent the practice's technical credibility in those forums. Beyond architecture, you shape strategy and roadmaps, establish standards and reference architectures, mentor and elevate the architect community, and are ultimately accountable for ensuring the firm delivers AI/ML infrastructure that meets business SLAs, controls cost, scales to frontier workloads, and creates lasting business value.
THE WORK- Set the overarching technical vision and strategy forcomputeinfrastructure supporting large-scale AI/ML systems,establishingthe direction that senior and lead architects build upon.
- Own the most complex, high-stakes architecture decisions acrosscompute, networking, storage, orchestration, and model serving, rationalizing multipleviableoptionsand making authoritative choices aligned to client situations, standards, and strategicobjectives.
- Architect and hands-on prototype large-scale, cost-optimized compute and distributed training systems - building reference implementations, proofs-of-concept, and benchmarks tovalidatedesigns before they scale.
- Define reference architectures, standards, and architectural patterns that scale across engagements, and personally implement the foundational tooling, infrastructure-as-code, and automation that anchor them.
- Lead enterprise-scale architecture assessments and design reviews,gettinghands-on in the environment tovalidatefindings, profile real workloads, anddemonstrateoptimization opportunities.
- Shape and steward the AI infrastructure roadmap and technology strategy, planning capacity, scaling, and technology evolution in step with long-term business goals.
- Identify, evaluate, and hands-on pilot promising emerging technologies and innovations,buildingand testing them in real conditions to judge where and when they belong in a solution.
- Drive hands-on performance and cost optimization of the computational stack, profiling GPU/computeutilization, tuning distributed training and model-serving workloads, and engineering improvements to meet SLAs while controlling cost.
- Serve as the principal authority acrosshyperscalercloud platforms, with current, hands-onexpertisein AI/ML services, accelerators, interconnects, and cost levers, and breadth across multiple providers.
- Lead deep, hands-on troubleshooting and root-cause analysis of the most complex issues across the stack - hardware, networking, software, and models - resolving the problems others cannot and codifying the fixes.
- Cultivate and lead relationships with infrastructure partners and partnering organizations, securingearly access, influence, and insight, andrepresentingthe practice's technical credibility in those forums.
- Provide executive- and client-level technical advisory, translating complex infrastructure trade-offs into clear, defensible recommendations tied to business outcomes.
- Define monitoring, observability, and reliability strategy acrossInfraOpsandMLOps, and implement the instrumentation, SLAs, SLOs, and cost/performance governance forproductionAI/ML systems.
- Ensure enterprise integration, security, compliance, and regulatory alignment of AI/ML infrastructure across the firm's solutions.
- Mentor, elevate, and grow the architect community, developing senior and lead architects through hands-on pairing, design collaboration, and code/architecture reviews.
- Champion cost-efficiency and value realization, ensuring infrastructure not only performs and scales but demonstrably moves the needle for the organizations it serves.
QualificationEDUCATION- • Bachelor's Degree in ComputerScience, ComputerEngineering, related Engineering field
BASIC (REQUIRED) QUALIFICATION- Significant experience in coding, building, monitoring,troubleshooting applicationsof AI/ML models; selecting, designing and infrastructurefor deployingand running themon premiseor on public cloud.
- Strong understanding of AI and machine learning as a subject.
- Strong understanding of computinginfrastructure asubject, preferred knowledge of AI infrastructure.
- Well versed and proven experiencein programming languages such as Python, Java, or C++.
- Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication and collaboration skills.
- Longstanding experience in AI/ML infrastructure engineering or related roles on ahyperscalerplatform for deploying large scale solutions.
- Proven experience in leading and managing AI projects and teams.
- Strong project management skills, with the ability to manage multiple projects simultaneously.
- Demonstrated experience in evaluating and selecting AI technologies and frameworks.
- Ability to work with cross-functional teams and drive project alignment.
LocationsLondon
Berlin
Madrid
Paris
Additional InformationEqual Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
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