Solution Architect with Pharma R&D Experience

  • Raritan, NJ
  • Posted 2 days ago | Updated 22 hours ago

Overview

On Site
USD60.0/HOURLY - USD74.0/HOURLY
Accepts corp to corp applications
Contract - W2
Contract - 6 Month(s)

Skills

Collaboration
Information security
Data-flow diagrams
Software architecture
Data modeling
Integration architecture
Infrastructure architecture
Machine Learning Operations (ML Ops)
Application lifecycle management
TLM
System integration
Lean methodology
Asset management
IO
Confluence
Business analysis
Business analytics
Pharmaceutics
Research and Development
Apache Kafka
Extract
transform
load
API
Streaming
RDBMS
Content management
GxP
Process modeling
Process management
Business process management
Robotic process automation
Computer networking
Storage
Database
Management
Articulate
Roadmaps
UI
WebKit
Deep learning
TensorFlow
PyTorch
Generative Artificial Intelligence (AI)
Natural language processing
Large Language Models (LLMs)
Machine Learning (ML)
Data Science
Training
Evaluation
Optimization
IaaS
Cloud computing
Amazon Web Services
Google Cloud
Google Cloud Platform
Microsoft Azure
Python
Java
Problem solving
SANS
Artificial intelligence

Job Details

Roles and Responsibilities:

  • Partner with Product teams, Client Technology Services and other architects to design scalable, flexible and supportable technical systems that drive business value in support of Regulatory Strategy and Intelligence

  • Develop architecture artifacts in collaboration with business and Client technology product owners, lead engineers, platform owners, R&D Architecture, Information Security, Quality and Technology Services stakeholders.

  • Artifacts for each project include the business context diagram, process overview, data flow diagram, application architecture, data model overview, integration architecture, infrastructure architecture and ML and ML Ops architectures.

  • Responsible for architecture alignment to Regulatory, Enterprise and R&D technology strategies, patterns and standards

  • Ensure Product roadmaps align to Regulatory strategy, established architectural principles and patterns, and enterprise ALM/TLM requirements.

  • Enable business at scale through simplification of the application landscape, system integration and intelligent automation.

  • Capture architecture and design information and decisions using Client-standard tools (Lean IX, SAXpress, Asset Management, Draw-IO, AMT, Confluence, MS Teams)

Education:

  • BA/BS degree in a technical, engineering or scientific field

  • AWS-Certified Solutions Architect certification required

  • AWS Well-Architected Framework certification desirable

  • AWS Certified Machine Learning Specialty certification desirable

Experience and Skills:
Required:

  • Knowledge of Regulatory data, content and terminology used in pharmaceutical development

  • 5+ years of experience as a Solution Architect with Pharma R&D Experience

  • 5+ years of experience in integration design and operationalization (REST APIs, Kafka, ETL, data pipeline design, API gateways, data streaming)

  • 5 years of experience working with structured RDBMS and content management platforms

  • Experience architecting regulated systems (GxP, HPIAA, GDPR, etc)

  • 2-3 years of experience architecting digital automation solutions using BPM, RPA, NLP and ML

  • Knowledge and skills in computer, networking, storage, database and AWS machine learning services as well as AWS deployment and management services.

  • Experience leading technical conversations, workshops and works to remove ambiguity, drive consensus and reach decisions across stakeholders

  • Proven ability to understand and articulate business requirements, direction, and initiatives.

  • Experience surfacing technical requirements and building IT product roadmaps

Skills Required:

  • Deep Learning: Proficiency in frameworks like TensorFlow, PyTorch, or similar tools for developing generative AI models.

  • Natural Language Processing (NLP): Understanding of large language models (LLMs), their training, and fine-tuning.

  • Machine Learning & Data Science: Knowledge of model training, evaluation, and optimization techniques.

  • Cloud Infrastructure: Familiarity with cloud platforms (AWS, Google Cloud Platform, Azure) for scaling and deploying AI solutions.

  • Programming: Strong coding skills in Python, Java, or similar languages used for AI development.

  • Problem-Solving: Ability to tackle complex business challenges and provide actionable AI-based solutions.

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.