AI Engineering Director

AI Engineering Director 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. Benefits 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. 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. Must be authorized to work in the U.S. without the need for employment-based sponsorship now or in the future. A&M will not sponsor applicants for U.S. work visa status for this role. #J-18808-Ljbffr