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Director, AI Engineering & Architecture, GESS - Global Capability Center

Director, AI Engineering & Architecture, GESS - Global Capability Center

Alvarez & Marsal
12-14 Years
Not Disclosed
Early Applicant
  • Posted 12 hours ago
  • Be among the first 10 applicants

Job Description

Description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with entrepreneurial, action and results-oriented professionals. We take a hands-on approach to solving our clients problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work - guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity - are why our people love working at A&M.

The Team

The Global AI & Knowledge Organization (GAIKO) is A&M's central engine for AI strategy, enablement, and knowledge infrastructure. Led by the Chief AI & Knowledge Officer, the team bridges firm strategy and frontline delivery, responsible for how A&M adopts, governs, and scales AI across its practices and geographies. The team's mandate spans the full lifecycle of AI at A&M: from rolling out enterprise tools like Claude to thousands of practitioners across the US, Australia, and Europe, to building the platforms and governance frameworks that ensure AI work is reusable, compliant, and compounding in value over time.

How You Will Contribute

  • Recruit, develop, and grow a global bench of Solution Architects, Applied AI Engineers, platform/config engineers, and DevOps engineers
  • Lead the design and delivery of enterprise LLM applications, agents, complex skills, and AI apps that create measurable business value across the firm
  • Set the architectural direction for A&M's custom AI product suite, including agent platforms, specialized skills, and internal AI applications
  • Establish and enforce standards for software development, CI/CD, testing, release gating, infrastructure automation, and reproducibility across every team building on the platform
  • Establish MLOps practices: model and prompt/agent versioning, evaluation pipelines, monitoring, and automated retraining where custom models are in use
  • Own the security posture for AI applications and platforms, including data privacy, access control, credential management, model risk, and secure SDLC
  • Drive build-vs-buy decisions across LLM providers, enterprise AI platforms, and vendor tools
  • Communicate technical tradeoffs, risk, and roadmap progress to senior firm leadership in business terms
  • Stay ahead of emerging AI capabilities - agentic architectures, RAG, fine-tuning, knowledge graphs - and run proofs of concept that inform the platform roadmap

Qualifications

  • 12+ years in software engineering, platform engineering, or applied AI engineering, including 5+ years leading technical teams
  • Demonstrated track record of building and scaling an engineering organization from the ground up
  • Deep hands-on background in software architecture, with credibility to review and challenge technical designs from senior engineers and architects
  • Hands-on experience with modern AI/LLM application architecture: agent frameworks, RAG, prompting, evaluation, fine-tuning, vector databases, and embeddings
  • Experience with SaaS platform/config engineering (e.g., Claude, ChatGPT, Gemini, Copilot) as well as custom application development built directly on LLM provider APIs, DevOps, CI/CD, and infrastructure automation
  • Experience with API key management, secrets management, and credential governance across multiple AI/LLM providers
  • Experience with major cloud platforms (AWS, Azure, or GCP) and modern data platforms
  • Experience with knowledge graph design and implementation (e.g., Neo4j, graph schemas/ontologies, graphbased retrieval) is a plus
  • Track record of embedding security and risk management into engineering practice, ideally in a regulated or professional services environment
  • Experience operating a global, distributed engineering team across time zones
  • Bachelor's degree in Computer Science, Engineering, or related field required; Master's preferred

Your journey at A&M

We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person's unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career. We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.

More Info

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Key Skills

embeddings

credential governance

knowledge graph design

API key management

evaluation fine-tuning

vector databases

Claude

platform engineering

CI CD

RAG prompting

ChatGPT

custom application development

secrets management

Copilot

AI LLM application architecture

SaaS platform config engineering

agent frameworks

applied AI engineering

About Company

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