AI Platform Architect, Strategy and Enablement

EisnerAmper•Philadelphia, PA

1d•Hybrid

About The Position

EisnerAmper is seeking an AI Platform Architect, Strategy & Enablement who will serve as the technical backbone of EisnerAmper’s AI transformation, owning the performance, reliability, and cost-efficiency of the EisnerAI Platform. This role will own and execute AI Platform strategy, defining the multi-year roadmap, cross-service-line capability, and coherence that position the platform as a strategic asset, scaling to 1,000 deployed AI agents across every solution, from intelligent tax preparation to agentic audit workflows. The role will build model lifecycle, evaluation, and multi-vendor orchestration as usage expands across every team. Reporting to the Chief AI Officer, this is a high-impact, high-visibility role at the intersection of platform architecture, AI engineering, and strategic operations. The critical dimensions of this position are internal - elevating platform fluency and technical depth across teams and external — cultivating strategic partnerships across the hyperscaler and AI vendor ecosystem to extend platform capability into wide ecosystem integration opportunities.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field
10+ years of experience in technology strategy, enterprise architecture, or platform/product leadership including experience as a Chief Architect or Enterprise Solutions Architect with a demonstrated record of scaling platforms across multiple business units
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
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 U.S. We are unable to sponsor or take over sponsorship of an employment Visa for this position now or in the future.

Nice To Haves

Master's degree preferred (Computer Science, AI/ML, Cloud Architecture, or MBA with technical focus)
Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent certifications strongly preferred
Data Platforms: ADLS Gen2, Cosmos DB, Azure SQL, Azure Synapse/Databricks for analytics and data engineering
AI Search & RAG: Vector search, semantic ranking, knowledge mining, and retrieval pipeline optimization
Governance & Compliance Tooling: Microsoft Purview, Azure Policy, data lineage, and audit logging frameworks
Monitoring & Observability: Azure Monitor, Application Insights, Log Analytics, custom dashboards (Power BI, Grafana)
Programming Languages: Python, C#, TypeScript, SQL, Bicep/Terraform
DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes, CI/CD pipeline design
Cost Management: Azure Cost Management, FinOps practices, token-level cost tracking and optimization
Proven track record of designing and implementing data governance frameworks and compliance controls at enterprise scale
Experience managing cloud cost optimization initiatives with demonstrated savings outcomes
Demonstrated experience mentoring technical and non-technical teams across organizational boundaries, and experience 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
Demonstrated experience translating governance, risk, or compliance requirements into platform-level controls or operational practice

Responsibilities

Own and Execute AI Platform Strategy
Own the multi-year platform roadmap — architecture, model lifecycle, and governance-as-code — scaling the EisnerAI Platform on Azure toward 1,000+ deployed agents while ensuring Tax, Audit, Advisory, and Outsourcing build on one coherent foundation.
Define and enforce model lifecycle standards (active, legacy, deprecated, retired) and evaluation benchmarks across the firm's multi-LLM environment, turning vendor and model choices — GPT-4o, o3, and what comes next, into a deliberate portfolio strategy rather than ad hoc adoption.
Own the connection between the EisnerAI Platform and the firm's broader technology ecosystem (ETI), establishing this bridge proactively rather than retrofitting it once scale makes it expensive.
Ensure the platform roadmap and standards account for both B2B and B2C dimensions of the firm's AI use — firmwide client service delivery as well as direct-to-client and wealth management contexts.
Lead Platform Strategy and Architecture
Architect and evolve the platform's core data, application, and agentic layers on Azure AI Foundry, establishing the reference architecture and technical standards that govern how every solution from intelligent tax preparation to agentic audit workflows gets built.
Codify AI and data governance (NIST AI RMF, PCAOB, Section 7216, and emerging requirements including the EU AI Act) into enforceable platform-level controls and automated compliance checks, in partnership with the firm's existing AI governance function.
Lead AI performance engineering across the firm's LLM ecosystem, benchmarking models for accuracy, latency, cost, and quality, and directing routing and optimization strategy to continuously lower cost-per-agent without sacrificing output quality.
Build and Operate Cross-Cutting Capability Enablement
Build and operate the platform's real-time performance monitoring layer, hallucination rates, retrieval precision, adoption, and cost-per-interaction, as a shared capability every service line draws on rather than one each team rebuilds independently.
Own identity, access, and security controls for AI systems and agents firmwide, establishing the guardrails that let Tax, Audit, Advisory, and Outsourcing scale their own use cases safely on shared infrastructure.
Deliver executive and board-level dashboards translating platform performance, adoption, and cost into business value narratives, and mentor technical and business teams across IT, AI Advisory, and service lines to build platform fluency firmwide.