Biopharma CMC Solution Engineer and Sales Support

Description

The company builds data, analytics and AI/ML solutions for biopharma and life sciences clients, covering everything from cloud data architecture to automated capture of data from scanned documents.

You will be the team's subject matter expert, bringing biopharma depth to sales, pre-sales and business development work with the data science, engineering and delivery teams.

Preferred experience is 5+ years.

Responsibilities

• Bring working knowledge of biopharma process development, large molecules, manufacturing, QA/QC and MSAT, along with the wider biopharma value chain.
• Understand how biopharma development and manufacturing workflows run, from upstream and downstream steps through scale-up, tech transfer, process characterization and optimization.
• Work comfortably within GMP settings, including quality systems, validation, deviations, CAPA, change control, batch records and regulatory compliance.
• Understand analytical testing, lab workflows, quality control and manufacturing performance targets.
• Spot operational problems, process waste, compliance gaps and improvement opportunities across the biopharma value chain.
• Join customer discovery calls, stakeholder meetings, technical discussions and requirement-gathering sessions alongside sales teams.
• Learn each client's business goals, operational pain points and technology needs, then suggest suitable solutions.
• Help sales teams position the company's technology services, data solutions, AI/ML capabilities and digital transformation offerings.
• Add domain input to sales strategy, account plans, opportunity qualification and solution positioning.
• Give domain-focused presentations, solution walkthroughs and demos to prospects and existing customers.
• Turn complex biopharma workflows and technical ideas into clear business use cases and solution stories.
• Build industry-specific scenarios showing how technology can raise process efficiency, quality, manufacturing performance and decision-making.
• Support proof-of-concept work, pilot projects and solution validation.
• Answer customer questions on biopharma processes, domain needs, fit and business value.
• Find places where data science, advanced analytics, AI/ML and GenAI can improve biopharma development and manufacturing.
• Shape use cases for process data analysis, manufacturing analytics, process monitoring, predictive maintenance, quality analytics and process optimization.
• Work with data science and engineering teams to turn domain problems into analytical use cases and technical requirements.
• Help develop use cases that combine process, lab, manufacturing and quality data with operational reporting.
• Assess how digital tools can support data-driven decisions, process understanding, efficiency and quality.
• Check that proposed solutions match real biopharma workflows, data requirements and regulatory considerations.
• Contribute to technical proposals, presentations, statements of work, RFP and RFI responses and other pre-sales documents.
• Convert client needs into functional requirements, business use cases and solution specifications.
• Work with technology, data engineering, AI/ML and delivery teams to judge feasibility and scope, including for the company's CPV platform products.
• Provide domain input on architecture, implementation approaches, project estimates and delivery plans.
• Create reusable industry-specific presentations, case studies, use cases and sales enablement material.
• Earn the trust of stakeholders in process development, manufacturing, MSAT, QA/QC, lab operations, data science and digital transformation.
• Help business and technical teams reach a shared view of requirements.
• Explain the business impact, operational benefits and possible limits of proposed solutions.
• Collect customer feedback and track emerging needs, industry trends and chances to expand services.
• Support long-term client relationships and business growth.
• Give domain guidance during solution design, proof-of-concept builds and customer presentations.
• Confirm that proposed use cases fit actual biopharma processes and customer needs.
• Keep up with developments in biopharma manufacturing, quality systems, digital transformation and data-driven operations.

Requirements

• At least 5 years in biopharma, biotechnology, pharmaceutical or life sciences, with relevant work in process development, manufacturing, QA/QC, MSAT or related areas.
• Deep expertise in one or more of: process development (upstream and downstream processing, characterization, scale-up, optimization, tech transfer); large molecules (biologics, mAbs, recombinant proteins and other large-molecule modalities); manufacturing (GMP practice, batch processes, production workflows, performance); QA/QC (quality systems, deviations, CAPA, change control, validation, analytical testing, compliance documentation); MSAT (manufacturing support, tech transfer, process validation, troubleshooting, process monitoring, continued process verification); or data science and analytics (data analysis, statistics, process and manufacturing analytics, AI/ML in life sciences).
• Ability to link biopharma business and operational problems to technology-based solutions.
• Customer-facing experience in pre-sales, solution or technical consulting, business development support, or industry presentations.
• Strong communication, presentation, stakeholder management and problem-solving skills.
• Ability to explain scientific, manufacturing, quality and data concepts to both technical and non-technical audiences.
• Experience working across scientific, operational, commercial and technology teams.