Smart Manufacturing – Solution Architect

Jobtailor; Kolkata District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Jobtailor in India seeks a senior Pharma digitalization consultant to lead large-scale transformation programs across pharma manufacturing. You will shape problem statements, value cases, and target architectures while steering delivery strategy and executive communications.

Responsibilities include governance across sites, paperless manufacturing, lab transformation, and end‑to‑end data integration with MES/ERP/LIMS/QMS ecosystems.

Qualifications

• 10–14 years in Pharma/Life Sciences manufacturing digitalization with consulting delivery leadership.
• MBA or an equivalent qualification from a top tier/reputed institute.
• Experience across at least two of MES/eBR, LIMS, or eQMS/QMS.
• Exposure to ISA‑95/ISA‑88 and manufacturing data contextualization.
• Experience with cloud data platforms and model governance in regulated settings.

Responsibilities

• Lead discovery workshops to shape problem statements, value cases, and roadmaps.
• Own proposal response strategy, estimation, and development of demos.
• Outline delivery approach, risks, pricing inputs, and POVs/demos.
• Lead multi-workstream delivery governance across sites and vendors.
• Drive paperless manufacturing and lab transformation initiatives.
• Define integration blueprints across MES, ERP, LIMS, QMS, Historian, SCADA.
• Identify and lead AI/advanced analytics use cases with governance and rollout.
• Engage CXO-level discussions and provide executive‑level recommendations.

Skills

Pharma/Life Sciences

Consulting delivery leadership

ISA-95/ISA-88 knowledge

Agile delivery

AI analytics in manufacturing

MLOps in regulated settings

Education

Bachelor's/Master's in engineering/technology/pharma

MBA or equivalent

Tools

Werum PAS‑X

PharmaSuite

Opcenter Pharma

Job description

Responsibilities

• Lead discovery workshops to shape problem statements, value cases, target architecture, and transformation roadmaps for pharma manufacturing
• Own proposal response strategy, solutioning, estimation, delivery approach, risk assumptions, pricing inputs, and development of reusable POVs/demos
• Lead delivery estimation and planning across work breakdown, resourcing, timelines, delivery model, and quality gates
• Act as trusted advisor by bringing strong consulting capabilities, and proven delivery methodologies to influence decision‑making through executive communication and structured recommendations
• Own multi‑workstream delivery governance across sites; manage stakeholders, vendors, and distributed teams
• Drive paperless manufacturing—requirements and solution design across eBR/eMBR, recipe/batch execution, materials & genealogy, weigh & dispense, and exceptions handling
• Lead lab transformation—sample lifecycle, test workflows, stability, reporting/COA—and standardize QC processes and data models
• Lead deviations, CAPA, change control, audits, training, document control, and supplier quality digitization with audit‑ready workflows
• Define integration blueprints across MES, ERP, LIMS, QMS, Historian, and SCADA, with contextualized data architecture for end‑to‑end traceability
• Identify and lead AI/advanced analytics use cases (deviation insights, drift detection/predictive quality signals, process optimization, reliability analytics) with governance, traceability, and controlled rollout

Requirements

• 10–14 years in Pharma/Life Sciences manufacturing digitalization with consulting delivery leadership
• Bachelor’s/master’s in engineering/technology/industrial/Pharma/Chemical or related fields
• MBA or an equivalent qualification from a top tier/reputed institute
• Strong experience across at least two of MES/eBR, LIMS, or eQMS/QMS
• Pharma MES experience (Werum PAS‑X, PharmaSuite, Opcenter Pharma) is a plus
• Experience of managing discussions with clients, CXO level engagements, advisory roles
• Exposure to ISA‑95/ISA‑88, MESA standards, manufacturing data contextualization, IIoT/historian integrations
• Experience with cloud data platforms, MLOps concepts, and model monitoring/governance in regulated settings
• Agile delivery (Scrum/SAFe), Lean/Six Sigma; alliance/vendor ecosystem experience; building demos/POVs
• AI enablement experience: delivered/led 1–2 analytics/AI initiatives (PoC/MVP/scale) in manufacturing/quality contexts