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

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