AI Platform Architect
About The Position
At EisnerAmper, we look for individuals who welcome new ideas, encourage innovation, and are eager to make an impact. Whether you’re starting out in your career or taking your next step as a seasoned professional, the EisnerAmper experience is one-of-a-kind. You can design a career you’ll love from top to bottom – we give you the tools you need to succeed and the autonomy to reach your goals. EisnerAmper is seeking an AI Platform Architect 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 is purpose-built to accelerate our journey to 1,000 deployed AI agents by designing and optimizing the infrastructure that powers every solution—from intelligent tax preparation to agentic audit workflows. The Platform Architect will benchmark and evaluate LLMs, codify AI and data governance into platform guardrails, build executive-grade reporting, and relentlessly drive cost and performance optimization across the entire AI stack. Reporting to the AI Development Lead, this is a high-impact, high-visibility role at the intersection of architecture, AI engineering, and strategic operations. A critical dimension of this position is mentoring and developing talent across organizational boundaries—partnering with IT infrastructure teams, the AI Advisory service line, and functional business units to build platform fluency and AI capability firmwide.
Requirements
- Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field
- 8+ years of experience in cloud platform architecture, infrastructure engineering, or AI/ML platform development
- 5+ years of hands-on experience with Microsoft Azure services (AI Foundry, Azure OpenAI, Cosmos DB, ADLS, Purview, AI Search)
- 3+ years of experience benchmarking, evaluating, and optimizing LLM-based systems in production environments
- 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, including IT, advisory, or consulting functions
Responsibilities
- Architect and scale the EisnerAI Platform on Azure, designing core data, application, and agentic layers to support growth toward 1,000+ AI agents
- Codify AI governance policies (NIST AI RMF, PCAOB, Section 7216) into enforceable platform-level controls, automated compliance checks, and governance-as-code pipelines
- Serve as a technical mentor and cross-functional leader, elevating AI platform capabilities across IT, AI Advisory, and engineering teams
- Lead AI performance engineering across the firm’s LLM ecosystem — benchmarking models (GPT-4o, o3, etc.) for accuracy, latency, cost, and quality to drive model selection and routing strategy
- Build and operate a real-time AI performance monitoring layer tracking hallucination rates, retrieval precision, adoption, cost-per-interaction, and ROI
- Optimize prompts, model configurations, and routing strategies to maximize output quality while reducing token consumption and overall platform cost
- Own AI cost management across Azure AI Foundry and related services, implementing intelligent model routing, caching, and token budgeting to continuously lower cost-per-agent
- Ensure all AI deployments meet regulatory, risk, and firm data governance standards prior to production
- Deliver executive and board-level dashboards translating AI performance, adoption, and cost metrics into clear business value narratives
Benefits
- flexibility to manage your days in support of our commitment to work/life balance
- culture that has received multiple top “Places to Work” awards
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What This Job Offers
Job Type
Full-time
Career Level
Senior
