Principal Technical Architect – AI, Data Platforms & Cyber Security

Senior Principal Technical Architect – AI, Data Platforms & Cyber Security

Princeton, NJ & NYC, NY (Hybrid)

Job Summary: We are looking for a Principal Technical Architect with 15+ years of experience in enterprise architecture, data platforms, AI systems, cloud, and cybersecurity. The role will lead the design and evolution of enterprise data platforms and multi-agent GenAI systems, with a strong focus on security, governance, observability, automation, and enterprise AI adoption.

Responsibilities

AI & Multi-Agent Architecture:

Design end-to-end multi-agent AI pipelines using Pydantic contracts, asynchronous Python, and provider-agnostic LLM integrations.

Work with OpenAI APIs, Databricks Model Serving, and similar enterprise AI platforms.

Build graph-based execution frameworks, YAML rule engines, capability registries, and diagnostic retry mechanisms.

Implement human-in-the-loop validation, schema validation, DAG editing, and error-repair workflows.

AI Security & Guardrails:

Lead threat modeling, abuse-case analysis, prompt-injection and jailbreak protection, and red-team strategies for LLM and RAG systems.

Implement AI guardrails including payload masking, SQL validation, row-count limits, and automated PII/PCI detection.

Design secure identity and access patterns using OAuth 2.0, Okta, Entra ID, Service Principals, and token lifecycle management.

Data Platforms & Observability:

Architect large-scale Databricks platforms, migrations, discovery, and governance automation.

Design solutions using Unity Catalog, Workflows, Jobs API, Delta Lake, and Delta Sharing.

Implement fine-grained data access using RLS, dynamic column masking, and centralized data classification.

Design automated data quality and observability frameworks for incident detection, table onboarding, and file freshness monitoring.

Lead multi-cloud platform governance, resource optimization, and FinOps across AWS, Azure, and GCP.

Enterprise GenAI & Governance:

Define enterprise strategies for adopting developer AI tools such as GitHub Copilot and custom LLM assistants.

Establish frameworks to measure code quality, productivity, and ROI.

Develop architectural standards, reusable patterns, technical documentation, and engineering workshops.

Mentor engineering teams and support organization-wide AI adoption.

Oversee access recertification, SIEM logging, auditing, data residency, and vendor risk governance.

Required Skills & Qualifications

15+ years of experience in enterprise software engineering, data platforms, AI systems, technical architecture, and/or security architecture.

Proven experience designing scalable enterprise solutions with strong data protection and zero-trust security.

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

Strong experience with multi-agent AI, LLM architectures, OpenAI APIs, Databricks Model Serving, Async Python, Pydantic, and prompt engineering.

Strong knowledge of LLM threat modeling, prompt injection, jailbreak mitigation, AI guardrails, and RAG security.

Experience with OAuth 2.0, Entra ID, Okta, Service Principals, and Delta Sharing security.

Strong Databricks expertise including Unity Catalog, Workflows, Delta Lake, Jobs API, and PySpark.

Experience with RLS, dynamic column masking, PII/PCI classification, zero-trust access, SIEM logging, and audit trails.

Strong SQL and relational database experience.

Experience with data quality, data observability, and governance frameworks.

Strong cloud architecture experience across AWS, Azure, and GCP, including cloud security and FinOps.

Advanced Python, including asynchronous programming, along with C#, .NET Core, REST API architecture, and YAML-based rule engines.

Experience with enterprise developer tooling administration, infrastructure/licensing governance, and token lifecycle management.

Strong communication, executive presentation, technical leadership, and cross-functional collaboration skills.

Leadership Capabilities

Translate enterprise business requirements into secure, scalable, contract-first architecture.

Drive technology adoption, technical strategy, and organizational change.

Communicate architecture, security risks, and technology strategy to executive stakeholders.

Drive cost optimization and operational risk reduction while maintaining strong security and compliance.