Solution Architect - AI/GenAI, Data & Statistical || FTE at NJ Jersey City, NJ, US

• Posted 2 days ago

• Updated 2 hours ago Full Time On-site Depends on Experience Fitment Dice Job Match Score™ 🔢 Crunching numbers... Job Details Skills Solution Architect AI GenAI Data Statistical AI/ML frameworks statistical modelling LLM architectures RAG pipelines agentic frameworks NLP computer vision Solution Architect AI GenAI Data Statistical AI/ML frameworks statistical modelling LLM architectures RAG pipelines agentic frameworks NLP computer vision Summary Solution Architect - AI / GenAI, Data & Statistical FTE role open at New Jersey Summary of the

Role:

The ideal candidate brings a strong technical architecture background, hands-on depth across AI, GenAI, data engineering, and statistical modelling, and the ability to translate complex business problems into scalable, production-grade solutions. The role requires a blend of architectural rigor, applied data science thinking, and client-facing credibility to design and guide the build-out of AI and data platforms across matrixed global organizations. This role owns the end-to-end solution architecture for AI, GenAI, and data-driven programs from use case discovery and technical design through deployment and scale. Deep exposure to Pharma, Clinical, and Life Sciences environments is a strong plus, and experience architecting solutions for the insurance domain will also be a good to have.

Key Responsibilities:

Solution Architecture & Design Own end-to-end solution architecture for AI, GenAI, and data platform initiatives, from requirements through production deployment Design scalable, secure, and cost-efficient architectures spanning cloud infrastructure, data pipelines, model serving, and application layers Define reference architectures, design patterns, and technical standards that can be reused across engagements Evaluate and select appropriate AI/ML frameworks, LLM providers, vector stores, and data platforms based on use case requirements Champion adoption of modern AI-assisted coding toolkits and spec-driven development methodologies to accelerate build quality and delivery velocity across engineering teams AI & GenAI Architecture Leadership Architect GenAI solutions including RAG pipelines, agentic workflows, prompt engineering frameworks, and fine-tuning strategies Design and oversee ML model deployment architectures, including MLOps pipelines, model monitoring, and governance frameworks Partner with Data Scientists and AI Engineers to translate statistical models and experimental notebooks into production-ready systems Establish responsible AI practices, including bias monitoring, explainability, and AI governance controls, within all architected solutions Data & Statistical Sciences Architect data foundations data lakes/warehouses, feature stores, and data governance frameworks that underpin AI and analytics use cases Guide the application of statistical methods (hypothesis testing, forecasting, causal inference, experimentation design) to ensure model and analytics rigor Oversee data quality, lineage, and integration architecture across structured and unstructured data sources, including real-world data (RWD) Define API-led and event-driven integration patterns connecting AI/data platforms with enterprise systems Stakeholder & Technical Engagement Act as the primary technical point of contact for client architecture and engineering stakeholders Translate business and clinical/regulatory requirements into technical solution designs and executable roadmaps Present architecture decisions, trade-offs, and technical recommendations to senior stakeholders and technical review boards Support pre-sales and solutioning efforts, including technical estimation, proposal design, and proof-of-concept development Team Leadership & Delivery Excellence Provide technical leadership and mentorship to AI Engineers, Data Engineers, and Data Scientists across onshore, offshore, and hybrid teams Establish architecture review processes, coding and design standards, and technical quality gates Drive continuous improvement through architecture retrospectives, technology radar reviews, and adoption of emerging AI/data tooling

Required Qualifications & Experience:

12+ years of progressive technology experience, with at least 5 years in a solution architecture role spanning AI, data, or digital platforms Demonstrable hands-on experience architecting and deploying GenAI, machine learning, or statistical modelling solutions in a commercial setting Strong grounding in statistical sciences (regression, forecasting, experimentation, causal inference) and their application to real-world business problems Experience architecting solutions within Pharmaceutical, Clinical Research, R D, or other regulated environments preferred Track record of taking AI/data solutions from proof-of-concept through to production-scale deployment

Technical Skills:

Hands-on expertise in GenAI, LLM architectures, RAG pipelines, agentic frameworks, NLP, computer vision, and AI governance frameworks: AI & Analytics Strong command of statistical and ML methods: predictive modelling, forecasting, experimentation/A-B testing, causal inference: Data Science & Statistics Data governance, MDM, API-led integration, data lake/warehouse architectures, real-world data (RWD): Data & Integration Cloud AI/data platforms (AWS, Azure, Google Cloud Platform), MLOps tooling, containerization, and CI/CD for model deployment Proficiency with modern AI-assisted/automated coding toolkits (e.g., Claude Code, GitHub Copilot, Cursor) and spec-driven coding methodologies for accelerating high-quality software delivery Familiarity with Veeva Vault, Oracle Clinical, or Argus Safety Clinical Systems is a plus

Jira, Confluence, Azure DevOps, ServiceNow Soft Skills & Leadership Attributes:

Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences Strong architectural and analytical thinking, with the ability to balance rigor against pragmatic delivery timelines High intellectual curiosity and comfort operating at the frontier of AI/GenAI tooling and techniques Collaborative leadership style with the ability to influence technical direction without formal authority Strong commercial acumen with a benefit-realization and outcomes-driven mindset

Preferred Qualifications:

Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or a related discipline Master's or PhD in Statistics, Data Science, Machine Learning, or a related quantitative field Cloud architecture certifications (AWS/Azure/Google Cloud Platform Solutions Architect) Relevant AI/ML certifications (e.g., TensorFlow, deep learning specializations, MLOps certifications) Experience working with CROs, CDMOs, regulatory agencies, or global pharma partners is a plus Thanks, IT First Source Employers have access to artificial intelligence language tools ("AI") that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id:

10116820

Position Id:

AY26_GS_8.9.1 Posted 2 days ago