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Solutions Engineer

Job in Aurora, Arapahoe County, Colorado, 80011, USA
Listing for: Norstella
Full Time, Seasonal/Temporary position
Listed on 2026-09-04
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Data Engineering
Salary/Wage Range or Industry Benchmark: 110000 - 170000 USD Yearly USD 110000.00 170000.00 YEAR
Job Description & How to Apply Below

Solutions Engineer

Company:
Norstella

Location:

Remote, United States

Date Posted:
Aug 18, 2026

Employment Type:

Full Time

Job : R-2137

Description

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:

  • Accelerate the drug development cycle

  • Assess competition and bring the right drugs to market

  • Make data driven commercial and financial decisions

  • Match and recruit patients for clinical trials

  • Identify and address barriers to therapies

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.

Job description:

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 work streams, 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, battle cards and enablement material that make every subsequent engagement faster and stronger.

  • Feed field intelligence back to product: recurring client requirements, competitive positioning, and the emerging patterns of what AI‑era work clients buy

Qualifications:

  • 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…

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