Search

AI Engineering Director

Alvarez & Marsal
locationTampa, FL 33607, USA
PublishedPublished: 5/20/2026
Engineering
Full time
Description

AI Engineering Director

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 AI Data Engineering Lead owns the design, build, and operations of the data layer underpinning all AI tools within the Global AI & Knowledge Organization. Reporting to the AI & Data Chief Product Officer, this leader connects AI capabilities to firm-wide structured systems (EDW, Salesforce, Workday) and unstructured knowledge stores (SharePoint, engagement repositories) while advising Business Units on integration approaches tailored to their unique data and security contexts.

The ideal candidate is both a strategic technology leader and a strong individual contributor who can actively code, architect solutions, mentor engineering teams, and partner with business stakeholders to drive AI innovation across the enterprise.

This leader will play a critical role in modernizing data layers, and operationalizing machine learning and generative AI capabilities in production environments.

How you will contribute

Data Layer Architecture
  • Lead design, build, and operations of the AI data layer across structured and unstructured sources, championing in-place access over unnecessary data movement
  • Architect governed pipelines connecting enterprise systems (EDW, Salesforce, Workday, SharePoint, ERP) to AI consumption layers; apply ETL/ELT and streaming where data movement is genuinely warranted
  • Enforce data modeling standards, metadata management, quality controls, and lineage tracking across the data layer
Unstructured Data & Knowledge Enablement
  • Own the strategy for making firm knowledge AI-accessible - SharePoint, document libraries, engagement deliverables, and BU content stores - via federated indexing and retrieval rather than bulk extraction
  • Design and operate RAG systems and AI search capabilities (Azure AI Search, hybrid search, semantic ranking) that surface relevant content while inheriting source system permissions
  • Develop chunking strategies, embedding pipelines, and index refresh processes; partner with Knowledge Management and BU content owners on taxonomy and relevance requirements
Data Governance & Security
  • Design a permission-aware data access model reflecting the firm's complex multi-BU structure - ensuring AI tools surface only what the requesting user is authorized to see, inheriting ACLs from source systems
  • Define data classification standards, access tiers, and audit controls in collaboration with Information Security and enterprise data governance; navigate conflicting access requirements across BUs
  • Embed governance and security controls directly into data layer architecture in support of the CoE's Responsible AI framework
Enterprise Integration & BU Advisory
  • Serve as technical owner for integrations with firm-wide systems; develop reusable connectors, API abstractions, and integration standards for the CoE tool portfolio
  • Advise BUs on connecting proprietary datasets and SharePoint content to CoE AI tools - including data readiness, security constraints, and governance requirements - without requiring BUs to surrender data ownership
Team Leadership
  • Lead and grow a team of data engineers: goal-setting, performance management, mentorship, and upskilling in RAG systems and AI search
  • Partner with the CoE Tech Lead on engineering standards, delivery processes, staffing, and capacity planning
Qualifications
  • 10+ years in data engineering, including enterprise-scale platform design; 3+ years in a people leadership role
  • Hands-on experience designing and operating RAG systems and AI search in production
  • Demonstrated experience enabling AI access to unstructured content (SharePoint, document repositories) using in-place or federated retrieval - not wholesale data centralization
  • Deep understanding of complex, multi-entity data governance and access control design; experience navigating conflicting security requirements across organizational boundaries
  • Strong proficiency in Python, SQL, and Azure data and AI services (ADF, ADLS, Azure AI Search, Microsoft Graph API)
  • Experience integrating enterprise systems (CRM, ERP, HCM, EDW) with AI or analytics platforms
Core Technical Skills

RAG, AI Search & Unstructured Data
  • Azure AI Search, hybrid/semantic search, federated retrieval, RAG architecture, embedding pipelines, LangChain / LlamaIndex, Microsoft Graph API, SharePoint indexing
Data Engineering & Integration
  • Python, SQL, Spark, Databricks, Airflow, dbt, ETL/ELT, Kafka, Delta Lake, Salesforce / Workday / ERP integration patterns
Governance, Security & Platform
  • Microsoft Purview, permission-aware retrieval, RBAC/ABAC, MIP sensitivity labels, audit logging, Azure Entra ID, Azure AI Foundry, CI/CD (GitHub Actions / Azure DevOps)
Preferred Qualifications
  • Professional services or consulting environment experience
  • Microsoft Copilot / Copilot Studio with custom connectors and SharePoint grounding
  • MCP (Model Context Protocol) server patterns for AI-to-data-source integration
  • Enterprise knowledge management practices in large, distributed organizations
  • Advanced degree in Computer Science, Data Engineering, or Information Systems
About the AI Center of Excellence

The AI CoE at Alvarez & Marsal is the firm's institutional hub for AI strategy, tooling, and governed deployment. The AI Data Engineering Lead is foundational to ensuring CoE platforms can reliably access the right data - structured and unstructured, enterprise-wide and BU-specific - in a manner that is secure, governed, and trusted across the firm.

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.

Regular employees working 30 or more hours per week are also entitled to participate in Alvarez & Marsal Holdings' fringe benefits consisting of healthcare plans, flexible spending and savings accounts, life, AD&D, and disability coverages at rates determined periodically as well as a 401(k) retirement savings plan. Provided the eligibility requirements are met, employees will also receive an annual discretionary contribution to their 401(k) retirement savings plan from Alvarez & Marsal. Additionally, employees are eligible for paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), ten federal holidays, one floating holiday, and parental leave. The amount of vacation and personal days available varies based on tenure and role type. Click here for more information regarding A&M's benefits programs.

The salary range is $225,000 - $275,000 annually, dependent on several variables including but not limited to education, experience, skills, and geography. In addition, A&M offers a discretionary bonus program which is based on a number of factors, including individual and firm performance. Please ask your recruiter for details.

#LI-LH1