AI Platform Architect, Strategy and Enablement

EisnerAmper•Boston, MA

About The Position

EisnerAmper is seeking an AI Platform Architect, Strategy & Enablement to serve as the technical backbone of its AI transformation. The role owns the performance, reliability, and cost-efficiency of the EisnerAI Platform, and sets and executes its strategy, multi-year roadmap, cross-service-line capabilities, and architecture. The platform is intended to scale on Azure toward 1,000 or more deployed AI agents across Tax, Audit, Advisory, and Outsourcing, supporting use cases ranging from intelligent tax preparation to agentic audit workflows. Reporting to the Chief AI Officer, this high-impact role sits at the intersection of platform architecture, AI engineering, and strategic operations. It builds model lifecycle, evaluation, and multi-vendor orchestration capabilities; connects the platform with the firm's broader technology ecosystem; and develops partnerships across hyperscalers and AI vendors. The role also elevates platform fluency and technical depth across teams, while accounting for both firmwide client service and direct-to-client and wealth management use cases. The position leads platform architecture on Azure AI Foundry, establishes standards for data, applications, and agentic systems, and implements governance and compliance controls in partnership with the firm's AI governance function. It also leads model performance, routing, and cost optimization; builds shared monitoring capabilities; owns identity, access, and security controls for AI systems and agents; and communicates platform performance, adoption, and cost in executive and board-level dashboards.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
At least 10 years of experience in technology strategy, enterprise architecture, or platform/product leadership, including experience as a Chief Architect or Enterprise Solutions Architect and a demonstrated record of scaling platforms across multiple business units.
At least 5 years architecting enterprise-scale solutions on Microsoft Azure, including AI Foundry, Azure OpenAI, Cosmos DB, ADLS, Purview, and AI Search, with direct accountability for platform reliability and cost at production scale.
At least 3 years leading LLM benchmarking, evaluation, and optimization programs in production environments, with a track record of translating model performance data into platform-wide selection and routing strategy.
Applicants must be authorized to work for any employer in the United States; the employer is unable to sponsor or take over sponsorship of an employment visa now or in the future.

Nice To Haves

Master's degree in Computer Science, AI/ML, Cloud Architecture, or an MBA with a technical focus.
Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent certifications.
Experience with data platforms including ADLS Gen2, Cosmos DB, Azure SQL, and Azure Synapse/Databricks for analytics and data engineering.
Experience with AI search and RAG, including vector search, semantic ranking, knowledge mining, and retrieval pipeline optimization.
Experience with governance and compliance tooling such as Microsoft Purview, Azure Policy, data lineage, and audit logging frameworks.
Experience with monitoring and observability tools such as Azure Monitor, Application Insights, Log Analytics, Power BI, and Grafana.
Experience with Python, C#, TypeScript, SQL, and Bicep/Terraform.
Experience with Azure DevOps, GitHub Actions, Docker, Kubernetes, and CI/CD pipeline design.
Experience with Azure Cost Management, FinOps practices, and token-level cost tracking and optimization.
Proven track record of designing and implementing enterprise-scale data governance frameworks and compliance controls.
Experience managing cloud cost optimization initiatives with demonstrated savings outcomes.
Experience mentoring technical and non-technical teams across organizational boundaries and owning vendor or model portfolio strategy in a multi-LLM environment.
Experience establishing or scaling a platform roadmap and adoption model from an engineering-first starting point.
Track record of leading through ambiguous, rapidly evolving technology landscapes.
Strong stakeholder management across engineering, governance, and business-line functions.
Experience translating governance, risk, or compliance requirements into platform-level controls or operational practice.

Responsibilities

Own and execute the AI Platform strategy and multi-year roadmap for architecture, model lifecycle, and governance-as-code, scaling the EisnerAI Platform on Azure toward 1,000 or more deployed agents.
Ensure Tax, Audit, Advisory, and Outsourcing build on a coherent shared platform foundation.
Define and enforce model lifecycle standards and evaluation benchmarks across the firm's multi-LLM environment, and establish portfolio, selection, and routing strategies for models and vendors.
Connect the EisnerAI Platform with the firm's broader technology ecosystem (ETI).
Ensure platform standards and roadmap address B2B and B2C use cases, including firmwide client service delivery, direct-to-client, and wealth management contexts.
Architect and evolve the platform's core data, application, and agentic layers on Azure AI Foundry, establishing reference architecture and technical standards.
Codify AI and data governance requirements, including NIST AI RMF, PCAOB, Section 7216, and emerging requirements such as the EU AI Act, into platform controls and automated compliance checks in partnership with the existing AI governance function.
Lead AI performance engineering across the LLM ecosystem, benchmarking accuracy, latency, cost, and quality and directing routing and optimization to lower cost per agent while maintaining output quality.
Build and operate shared, real-time platform performance monitoring for measures such as hallucination rates, retrieval precision, adoption, and cost per interaction.
Own firmwide identity, access, and security controls for AI systems and agents.
Deliver executive- and board-level dashboards that translate platform performance, adoption, and cost into business value narratives.
Mentor technical and business teams across IT, AI Advisory, and service lines to build platform fluency.
Cultivate strategic partnerships across the hyperscaler and AI vendor ecosystem.