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AI Solutions Architect
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Procal Technologies
Franklin Lakes, NJ (In Person)
Full-Time
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Job Description
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.