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AI Enabled Automation Architect (pharmaceutical manufacturing)

Vailexa Technology LLCIndianapolis, IN🇺🇸United StatesPosted 6 Aug 2026

Why This Role Stands Out

This role offers a unique opportunity to shape the future of pharmaceutical manufacturing by architecting cutting-edge AI-enabled automation solutions. If you are a seasoned DeltaV configuration expert with a passion for optimizing batch processes and driving innovation, you will thrive in this impactful, mid-senior position. Apply today to contribute to advancements in a critical industry.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Indianapolis, IN, United States
Posted
3 weeks ago

Job Description

Role- AI Enabled Automation Architect
Location- Indianapolis, IN onsite
Duration - 18 months
 
Required Qualifications
  1. Experience with tech transfer, manufacturing automation, recipe design, control strategies, and batch execution workflows; specifically batch process experience, not continuous process control.
  2. Minimum 6 years of hands-on, batch-specific DeltaV configuration experience (not continuous), plus working knowledge of MES, data integration, and digital manufacturing architectures.
  3. Pharmaceutical or life sciences manufacturing experience; Small Molecule experience specifically preferred, with biologics, advanced therapies, or multi-modality experience considered a plus.
  4. Capability in data modeling, information architecture, knowledge representation, or related digital-knowledge disciplines.
  5. Experience bridging process knowledge and digital execution systems without over-reliance on custom application development.
  6. Experience designing modular, reusable technical frameworks rather than one-off implementations.
  7. Hands-on experience with AI or machine learning tools in an regulated technical environment, with the aptitude and willingness to grow into more advanced AI-driven workflows (e.g. agentic architectures).
  8. Ability to work iteratively using real process examples, user feedback, and rapid learning cycles.
  9. Strong cross-functional engagement skills with automation, process engineering, operations, PT&E, quality, and related stakeholder groups.
Preferred Capabilities
  • AI-enabled analysis, decision support, or knowledge-system experience in regulated technical environments; particularly agentic architecture and coding experience (e.g. Claude Code, Codex).
  • Change-management, training, and governance experience to help operationalize adoption across functions.
  • Familiarity with data integrity principles (ALCOA+) and data governance frameworks.
  • Experience with Kneat, ValGenesis, or similar electronic validation management systems.

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