AI Solutions Architect

AI Solutions Architect

Franklin Lakes, NJ 07417

TECHNICAL SKILLS

Must Have

• Strong hands‑on software development experience (e.g., Python, APIs, SQL, cloud platforms).

• Proven experience designing and building AI or ML‑enabled solutions end‑to‑end.

• Experience integrating multiple data sources via APIs, connectors, or data pipelines.

• Solid understanding of analytics architectures, data modeling, and insight generation.

• Experience deploying solutions in enterprise environments with security and governance considerations.

Job Description:

• The AI Architect for the Client Excellence Office will be a hands‑on technical leader responsible for designing, building, and scaling AI‑enabled solutions that integrate across enterprise data sources to deliver actionable analytics, insights, and decision support.

• This role blends architecture, software engineering, and applied AI with a strong understanding of business operations, continuous improvement, and analytics.

Key Responsibilities

AI Architecture & Solution Design

·       Design end‑to‑end AI architectures that integrate multiple enterprise data sources (structured and unstructured) into scalable, secure AI solutions.

·       Define patterns for AI integration across platforms such as SharePoint, analytics tools, workflow systems, and internal applications.

·       Ensure solutions align with enterprise security, data governance, and responsible AI standards.

Hands‑On Development

·       Actively develop and deploy AI solutions using modern programming languages and frameworks (e.g., Python, SQL, APIs, cloud services).

·       Build data pipelines and connectors to ingest, refresh, and synchronize data automatically from source systems.

·       Prototype and productionize AI capabilities such as natural language querying, document intelligence, analytics copilots, and insight generation.

Data & Connectors

·       Design and implement connectors to enterprise systems (e.g., repositories, learning systems, workflow tools, analytics platforms).

·       Architect data flows that support near‑real‑time updates and minimize manual data maintenance.

·       Partner with data engineering and analytics teams to optimize data models for AI use cases.

Analytics & Insights Enablement

·       Apply AI and advanced analytics to surface insights, trends, and leading indicators that support operational excellence and decision‑making.

·       Enable conversational and embedded analytics experiences where users can ask questions and receive AI‑driven insights within their workflow.

·       Support multilingual and global user needs where required.

Integration & Embedding

·       Enable AI solutions to be embedded within existing platforms and tools used across Client.

·       Design AI components that support persistent context, conversation history, and follow‑up questions.

·       Collaborate with product owners to integrate AI into dashboards, portals, and enterprise tools.

Collaboration & Enablement

·       Partner closely with Client Office leaders, analytics teams, IT, and platform owners to translate business needs into technical solutions.

·       Define best practices, reusable components, and technical standards for AI across the Client ecosystem.

·       Mentor developers and analysts on AI solution development and integration patterns.

Required Qualifications

Technical Skills

·       Strong hands‑on software development experience (e.g., Python, APIs, SQL, cloud platforms).

·       Proven experience designing and building AI or ML‑enabled solutions end‑to‑end.

·       Experience integrating multiple data sources via APIs, connectors, or data pipelines.

·       Solid understanding of analytics architectures, data modeling, and insight generation.

·       Experience deploying solutions in enterprise environments with security and governance considerations.

AI & Analytics Experience

·       Practical experience applying AI for:

o   Analytics and insight generation

o   Natural language interaction with data and documents

o   Decision support and operational intelligence

·       Understanding of model lifecycle, monitoring, and continuous improvement in production environments.

Professional Experience

·       7+ years of experience in software engineering, data engineering, AI architecture, or related fields.

·       Demonstrated ability to move from concept to working production solutions.

·       Experience working in complex, matrixed enterprise environments.

Preferred Qualifications

·       Experience with enterprise collaboration and analytics platforms.

·       Familiarity with continuous improvement, operational excellence, or transformation programs.

·       Experience designing AI copilots, assistants, or embedded AI experiences.

·       Exposure to usage analytics, telemetry, and insight measurement for AI solutions.

What Success Looks Like

·       AI solutions that are deeply integrated, not standalone.

·       Minimal manual data upkeep through robust connectors and automated pipelines.

·       Measurable improvement in insight quality, speed to decision, and user adoption.

·       A scalable AI architecture that can grow with Client priorities.