Title: Process Development Consultant Anywhere Type: Contract Category: Manufacturing Industry: Life Sciences Workplace Type: Remote Reference ID: JN -042026-106275 Job Description: CONTEXT A growing medical device company specializing in steerable cardiac catheters is seeking an experienced Manufacturing Process Development & Scale‑Up Consultant. Reporting to the CTO (Head of R&D & Operations), the consultant will lead efforts to transition low-volume manufacturing to outsourced, scalable production, including site selection, knowledge transfer, pilot implementation, and full-scale launch. Ideal candidates bring big-company, multi-step catheter manufacturing expertise and a proven track record in outsourced medical device scale-up Responsibilities: DUTIES/EXPECTATIONS OF THIS ROLE Outsourced Manufacturer Selection & Onboarding - Identify and evaluate potential US and global manufacturing partners capable of scaling catheter production - Conduct site visits, due diligence, and comparative assessments for capacity, quality systems, and regulatory readiness - Support contracting, MSA negotiation, and alignment of manufacturing scope Knowledge Transfer & Pilot Program Design - Lead knowledge transfer sessions, ensuring clear documentation of current catheter assembly processes - Develop and manage pilot manufacturing protocols, including tolerances, throughput targets, and quality measures - Set success metrics and advance-to-production criteria for pilot outcomes Scale‑Up Planning & Execution - Architect scalability roadmap: process flows, capacity planning, supply chain logistics, and automation potential - Integrate quality systems, regulatory compliance, and process validation into scale-up transition - Oversee supplier onboarding, staff training, and site readiness for production ramp Continuous Improvement & Operations Enablement - Implement statistical process control (SPC), lean manufacturing practices, and quality analytics - Monitor operational KPIs during pilot and early production phases → adjust protocols for improvement - Enable cross-functional collaboration: Manufacturing, Quality, Supply Chain, R&D, and external partners Experience Requirements: MUST HAVES – QUALIFICATION SUMMARY · 10+ years in manufacturing process development, scale-up, and transfer in regulated medical device environments, preferably in catheters or steerable cardiovascular devices · Proven success managing outsourced manufacturing startups, from pilot through annual production volume (~10k units/year) · Strong familiarity with multi-step catheter assembly processes: extrusion, braiding, bonding, coating, final assembly · Experience conducting site qualification and knowledge transfers, driving pilot implementation and scale · Demonstrated ability to operate with objectivity and autonomy, ideal for high-ambiguity, scaling environments · Background at a large med-tech or medical device OEM · Expertise in lean manufacturing, SPC, ISO 13485, FDA/CE regulatory landscapes · Advanced degree in Engineering, Manufacturing, or related discipline Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range. W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.

• Work independently providing best-in-class delivery and integration services to a wide range of organizations and verticals • Act a trusted advisor to help lead customers to mature outcomes using next generation SIEM, log management, XDR and SOAR features and functionality • Provide knowledge transfer of Falcon LogScale NGSIEM to our customers

• Responsible for the planning, deployment, implementation, and operational support of the CrowdStrike platform’s AI capabilities • Focus specifically on leveraging Falcon’s Artificial Intelligence (AI) and Machine Learning (ML) technologies to enhance threat detection • Assist customers in optimizing AI-driven threat detection models and automated response workflows • Configure and tune machine learning algorithms to reduce false positives • Develop and implement AI-driven automation playbooks for security operations • Troubleshoot AI-related customer issues across small to large enterprises • Develop scripting and application solutions using Falcon APIs to enhance AI capabilities • Work closely with customers to interpret AI-generated alerts and findings • Support Incident Response teams with AI-powered threat hunting and forensic analysis • Develop and lead AI skills workshops for the Platform Professional Services team • Work collaboratively with the Platform Professional Services team to develop customer-facing AI collateral

Consultancy Contract. Project Start Date: May 2026. Project Duration: Six (6) months - Extension possible contingent on expansion of use cases Deadline for Applications: 20 April 2026 at midnight CET About CGIAR CGIAR is a global research partnership for a food-secure future. CGIAR science is dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources and ecosystem services. Its research is conducted closely with hundreds of partners, including national and regional research institutes, civil society organizations, academia, development organizations, and the private sector. Background and Objectives The CGIAR System Organization (SO) is implementing an AI Strategy to enable an Enterprise AI Transformation that strengthens governance, improves executive decision making, and increases operational efficiency in a highly volatile funding environment. While the SO benefits from a strong, Microsoft centered digital backbone, decision making and operational processes remain fragmented and largely retrospective, limiting the organization’s ability to anticipate risks, respond proactively, and reduce leadership burden. The AI Strategy introduces an AI enabled executive decision and operations layer that integrates data across core enterprise platforms—including ERP, CRM, Financial Planning & Analysis (FP&A), collaboration tools, and other enterprise and specialist systems introduced over time. The objective is to move beyond descriptive reporting toward proactive, model driven steering, using AI advisers to support leadership, strengthen institutional memory, and improve governance and operational outcomes across the organization. The objective of this consultancy is to provide product level coordination and hands on delivery enablement for Enterprise AI Transformation. The consultant will ensure that the AI Strategy is translated into a structured, governed, and phased product delivery, with clear milestones, aligned stakeholders, managed risks, and measurable outcomes. The role combines two complementary dimensions: - Working Agents Delivery: hands on delivery of the design, build, and operation of AI solutions, leveraging Microsoft low code platforms (notably Microsoft Copilot Studio and Microsoft Foundry), in close collaboration with internal teams and external vendors. - AI product coordination: structuring, coordinating, and governing AI initiatives across the System Organization to ensure coherence, prioritization, and alignment with enterprise governance and strategic objectives; and external vendors. 2. Scope of Work Reporting to the Senior Manager, Digital Transformation, and in close coordination with Finance, Governance, People & Culture, ICT, and senior leadership, the consultant will be responsible for the following: 2.1 Delivery Coordination and Technical Enablement - Deliver design, build, configuration, governance, and lifecycle management of AI agents, with a strong focus on Microsoft low code platforms (notably Copilot Studio and Foundry) and related Microsoft technologies. Where appropriate, identify and coordinate the involvement of additional specialist expertise to support complex or highly specialized components. - Support the integration of AI solutions with enterprise data sources and systems, ensuring architectural coherence, security, compliance, and alignment with enterprise data and AI standards. 2.2 AI Product Structuring and Governance - Translate the approved AI Strategy into a set of clearly defined Enterprise AI Transformation products, aligned with the agreed phased roadmap and governance model. - Define and maintain AI product workstreams for AI for Management & Governance and AI for Operations, including clear scope, sequencing, dependencies, and success criteria. - Establish and operate AI product governance structures, including decision making forums, escalation mechanisms, reporting cadence, and alignment with existing enterprise governance bodies. Act as the primary coordination point between external vendors, internal technical teams, and business stakeholders, ensuring clarity of scope, roles, and delivery expectations. - Coordinate and support the delivery of AI products, including executive AI advisers, decision support use cases, scenario modelling, institutional memory, and operational AI solutions. 2.3 Risk, Dependency, and Change Management - Identify and manage cross product risks and dependencies, including data readiness, security, capacity, and adoption risks. - Support change management activities to enable adoption of AI solutions, with a focus on senior leadership and governance users. 2.4 Vendor and Investment Oversight - Support oversight of external vendors and consultants, monitoring delivery against agreed scope, milestones, and outcomes. - Track delivery against the approved investment envelope and flag deviations or risks early. 3. Deliverables Indicative deliverables include: - Working agents in Copilot Studio and Foundry - Enterprise AI Transformation Product Plan - AI Product governance and reporting framework - Consolidated risk, dependency, and issue register - Regular status reports and executive dashboards - Inventory of deployed AI agents and documented AI use cases (as applicable) - Phase end reviews and lessons learned documentation Deliverables will be refined and agreed at contract inception 4. Timelines 5. Key Performance Indicators The consultant’s performance will be measured against the following Key Performance Indicators (KPIs). The technical lead will be responsible for monitoring and reporting on these KPIs. Renewal or re contracting will be conditional on documented performance against these indicators. - Quality of Work: Accuracy, completeness, and overall quality of submitted deliverables, including product plans, AI use cases, governance artefacts, and documentation. - Timeliness: Ability to meet agreed milestones and deadlines as outlined in the 6 month delivery timeline and any subsequently approved workplan. - Client and Stakeholder Satisfaction: Feedback from key stakeholders (senior leadership, governance users, functional teams, and technical counterparts) regarding professionalism, effectiveness, and collaboration. - Adherence to Scope and Budget: Delivery of agreed outputs within the approved scope, level of effort, and budget, with proactive management and early escalation of risks or deviations.