Senior Principal Technical Architect

TalentOla; Princeton (NJ); Hybrid; USD 180,000 - 240,000; Full time

Job summary

TalentOla in Princeton, NJ / NYC, NY is seeking a Senior Principal Technical Architect to lead architecture for enterprise data platforms, AI systems, and cybersecurity. The role combines hands-on design with executive leadership to scale GenAI solutions and ensure robust security controls.

The ideal candidate has 15+ years of experience in software, data platforms, and security architecture, with a track record of large-scale enterprise transformations across cloud ecosystems.

Qualifications

• Over 15 years of experience in software engineering, enterprise data platforms, AI systems, and security architecture.
• Proven track record of architecting scalable solutions adopted across large organizations with strong data protection and zero-trust security.
• Experience leading enterprise-wide technology adoption programs, platform migrations, and security governance frameworks.
• Strong collaboration and leadership skills across cross-functional and executive teams.

Responsibilities

• Architect Multi‑Agent AI Pipelines: design end-to-end, LLM-powered multi-agent frameworks using contracts and provider-agnostic models.
• AI Tooling & Scaffolding: build graph-based execution builders, dynamic YAML rules engines, capability registry patterns.
• Human-in-the-Loop Integration: implement validation and curation layers for DAG editing, schema validation, and error repair.
• 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, 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 token lifecycle/rotation management.
• Databricks Estate Architecture: lead large-scale data platform migrations, estate auto-discovery, and governance automation across Databricks workspaces.
• Data Governance & Zero‑Trust Access: enforce fine-grained authorization models including Row-Level Security, dynamic masking, and data classification in Unity Catalog.
• Data Quality & Observability Frameworks: design automated, multi-tiered data quality verification platforms with real-time incident detection and continuous file freshness tracking.
• Platform Governance & FinOps: oversee multi-cloud cost governance, resource optimization, and infrastructure governance to maximize ROI while maintaining compliance.
• Org‑Wide Transformation: define adoption strategies for developer AI tooling and establish measurement frameworks for code quality, productivity gains, and ROI.
• Enablement & Standards: conduct workshops, build best-practices documentation, create reusable architectural patterns, and mentor engineering teams.

Skills

Python

Databricks

LLM architectures

Threat modeling

Zero-trust security

Security governance

Cloud architecture

Leadership

Tools

OpenAI SDK

Delta Sharing

Unity Catalog

Okta/Entra ID

Job description

Senior Principal Technical Architect AI, Data Platforms & Cyber Security
Location- Princeton, NJ & NYC, NY (Hybrid)

Fulltime

Job Description: Principal Technical Architect AI, Data Platforms & Cyber Security

Position Title: Principal Technical Architect AI Systems, Data Platforms & Cyber Security
Department: Enterprise Architecture / Data, AI & Security Engineering
Experience Level: 15+ Years (Executive / Principal Level)

Role Overview

We are seeking a visionary and hands‑on Principal Technical Architect to lead the architecture, design, security, and strategic evolution of our Enterprise Data Platforms and Multi‑Agent GenAI Systems. In this role, you will bridge the gap between complex enterprise data engineering, modern cloud architecture, cutting‑edge Generative AI applications, and enterprise cybersecurity controls.

You will design zero‑touch automated data observability solutions, multi‑agent AI pipelines, zero‑trust data access patterns, and enterprise‑wide GenAI adoption frameworks. The ideal candidate brings a deep technical background in Databricks, cloud platforms, Python, contract‑driven LLM architectures, threat modeling for AI systems, and proven enterprise leadership in scaling and securing AI solutions across the organization.

Key Responsibilities

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.