Principal Technical Architect - AI, Data Platforms & Cyber Security

Job Title: Senior Principal Technical Architect AI, Data Platforms & Cyber Security
Job Location: Princeton, NJ
Job Type: Full-Time

Job Description:

1. AI Systems & Multi-Agent Architecture

Architect Multi-Agent AI Pipelines: Design end-to-end, LLM-powered multi-agent frameworks (deterministic + generative) using Pydantic contracts, asynchronous Python, and provider-agnostic model integration (e.g., OpenAI SDK, Databricks Model Serving).

AI Tooling & Scaffolding: Build graph-based execution builders, dynamic YAML rules engines, capability registry patterns, and structured diagnostic retry mechanisms for LLM agents.

Human-in-the-Loop Integration: Implement validation and curation layers that enable user DAG editing, schema validation, and error repair before scaffold generation.

2. AI Security, Risk & Guardrails

LLM Threat Modeling & Abuse Prevention: Lead abuse-case modeling, prompt injection defense, jailbreak mitigation, and red-teaming strategies for LLM agents and RAG architectures.

Output Guardrails & Data Protection: Implement payload masking, custom SQL validation layers, row-count caps, and automated PII/PCI detection to prevent data exfiltration via AI interfaces.

Identity & Access Governance: Architect hybrid identity flows (OAuth 2.0, Okta/Entra ID), Service Principal access patterns, and automated token lifecycle/rotation management (e.g., Delta Sharing tokens).

3. Enterprise Data Platforms & Observability

Databricks Estate Architecture: Lead large-scale data platform migrations, estate auto-discovery, and governance automation across Databricks workspaces (Unity Catalog, Workflows, Jobs API, Delta Lake, Delta Sharing).

Data Governance & Zero-Trust Access: Enforce fine-grained authorization models including Row-Level Security (RLS), dynamic column masking, and centralized data classification in Unity Catalog.

Data Quality & Observability Frameworks: Design automated, multi-tiered data quality verification platforms capable of real-time incident detection, automated table onboarding, and continuous file freshness tracking.

Platform Governance & FinOps: Oversee multi-cloud cost governance (AWS, Azure, GCP), resource optimization, and infrastructure governance to maximize ROI while maintaining compliance.

4. Enterprise GenAI Adoption & Governance

Org-Wide Transformation: Define and execute adoption strategies for developer AI tooling (e.g., GitHub Copilot, custom LLM assistants) and establish measurement frameworks for code quality, productivity gains, and ROI.

Enablement & Standards: Conduct technical workshops, build best-practices documentation, create reusable architectural patterns, and mentor engineering teams across divisions.

Compliance & Security Auditing: Oversee access recertification, SIEM logging/auditing mechanisms, and regulatory compliance (e.g., regional data residency and vendor risk governance).

Required Qualifications & Technical Expertise

Professional Experience

10+ years of progressive experience in software engineering, enterprise data platforms, AI systems, and technical/security architecture within high-volume enterprise environments.

Proven track record of architecting scalable solutions adopted across large organizations while maintaining high standards of data protection and zero-trust security.

Experience leading enterprise-wide technology adoption programs, platform migrations, and security governance frameworks.

Technical Stack & Competencies