RCI-BDX-3327 AI Architect (Medical Device)
Rangam is looking for RCI-BDX-3327 AI Architect (Medical Device) in Franklin Lakes, NJ.
This local job opportunity with ID 3704050804 is live since 2026-06-07 02:31:11.
Location: Franklin Lakes NJ
Job Title: AI Architect
Duration: 12 Months
This is a hybrid role (4 Days Onsite and 1 day remote per week | Mon - Thu: Onsite & Fri: Remote)
Manager's Update:
- Prior medical device/Regulated industry exp. would be helpful but not a deal breaker
- Must have exp. with deploy/deployment of AI data
- AI-Chatbots exp. is required
- Co-relate the data
- Able to work with digital platforms (Monday.com, SharePoint)
- Looking for a high level Architect
- Able to work with Data into meaningful insights
- This person needs to be a technical person
- This is not a software developer or a full-stack developer or a coder role
- Looking for 7+ years of exp.
- This person would be involve in IT + Business Operations System + Digital Applications
Must have skills:
- Monday.com
- AI Architecture
- Databricks
- Data Engineering
- Able to build interfaces
- Hands-on development
- Python
- Deployment
- Analytics
- This is not a strategy-only role. The ideal candidate can code, prototype, and deploy, while also defining scalable architectures and standards for AI across the BDE ecosystem.
- On site for 1 year in FLks AI Architect for the BD Excellence (BDE) 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 BDE.
- 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 BDE 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 BDE 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:
- Analytics and insight generation
- Natural language interaction with data and documents
- 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 BDE priorities.
- 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.