Solutions Engineer

The Solutions Engineer understands both the technology and the challenges our clients are trying to solve, and works with them to find the right solution. You partner with account executives across the research, development and commercial cycle, leading discovery, solutioning, demonstration and proposal, by understanding not just what our data is, but how it will work inside a client’s environment.

The work spans a spectrum: at one end, demonstrating and integrating our productised capability; at the other, bespoke co-development programmes with strategic clients, scoped through discovery and statements of work. You’ll start with an advise, scope and demonstrate mandate, and as client demand crystallises your remit will grow to include hands-on build, moving from a compelling demo to a running solution the client can see working against their own data.

Responsibilities:

Pre-sale technical partnership

• Support the sales organization by building an understanding of the client challenges: their clinical trial/research and commercial questions, data landscape, governance constraints, and AI ambitions, and mapping these to Norstella capabilities as applicable.

• Design and deliver compelling demonstrations tailored to the client’s actual use cases, not generic scripts.

Solutioning and bespoke engagements

• Scope proofs of concept and structured engagements, defining success criteria and evaluation plans with the client.

• Deliver bespoke engagements inside client environments through trial and hypercare, converting complexity into deployed, ongoing, repeatable solutions.

• Shape statements of work with commercial teams, covering workstreams, deliverables, assumptions, dependencies and risks, turning an ambiguous client ambition into a scoped, sellable engagement.

• Work alongside client engineering, IT and vendor teams through delivery. You are the technical face of Norstella inside the programme.

Enablement, reuse, and feedback

• Turn one-off client work into reusable IP: demo environments, playbooks, battlecards and enablement material that make every subsequent engagement faster and stronger.

• Domain knowledge of pharma and life sciences: clinical trials (site feasibility, protocol design), pipeline and asset intelligence, epidemiology, market access, or forecasting (e.g. PTRS, rNPV, consensus forecasting).

• 3-5 years in a solutions engineering, sales engineering, technical consulting or implementation role for a data, analytics or SaaS product, ideally with enterprise clients.

• Outstanding communication: you can present to a technical architect and a commercial VP in the same meeting and land with both.

• Strong discovery instincts: you ask the questions that reveal what a client is actually trying to do, and you listen more than you pitch.

• Comfort with ambiguity: the products, the market, and this role itself are all evolving. You treat that as the opportunity, not the drawback.

• Experience delivering work inside client environments, such as embedded engagements, professional services or consulting, is a plus.

Norstella is a premier and critical global life sciences data and AI solutions provider dedicated to improving patient access to life-saving therapies. Norstella supports pharmaceutical and biotech companies across the full drug development lifecycle - from pipeline to patient. Our mission is simple: to help our clients bring therapies to market faster and more efficiently, ultimately impacting patient lives.

Norstella unites market-leading brands - Citeline, Evaluate, MMIT, Panalgo, Skipta and The Dedham Group and delivers must-have answers and insights, leveraging AI, for critical strategic, clinical, and commercial decision-making. We help our clients, Norstella serves most pharmaceutical and biotech companies around the world, along with regulators like the FDA, and payers. By providing critical proprietary data supporting AI-driven workflows, Norstella helps clients make decisions faster and with greater confidence. Norstella’s investments in AI are transforming how data is consumed and decisions are made, disrupting inefficient legacy workflows and helping the industry become more efficient, innovative, and responsive to patient needs.