Senior Lead, Forward Deployed Engineer
GSK is hiring a Senior Lead, Forward Deployed Engineer for a remote role open to applicants in India. Level rates it ; you can apply on GSK.
Level's read on this job
- Level rates this forward deployed engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions prompt engineering, RAG and NLP among its tools and skills.
- GSK has 847 other open roles on Level.
- Posted in the last few days.
AI in this role
About the Role
Do you enjoy turning Medical Affairs opportunities into practical digital, data, analytics, and AI solutions? Can you work closely with business and technical teams, learn complex workflows, and contribute to rapid prototypes and production-ready capabilities?
As a Senior Lead, Forward Deployed Engineer, for Global Medical Affairs Digital & Tech, you will work alongside product teams, data scientists, GSK Strategic Partner engineering resources to build solutions that improve Medical Affairs solutions Data Generation, Scientific Communications, Medical Information, MSL Engagement and Insights. With support from experienced engineers and product leaders, you will contribute from discovery and rapid validation through production deployment, adoption, and continuous improvement.
The focus is on building working, trusted software and analytics that fit real workflows and deliver measurable Medical Affairs value.
Why This Role Exists
Global Medical Affairs needs hands-on engineers who can help connect business questions, scientific workflows, fragmented data, and scalable technology. This role combines customer collaboration, rapid engineering, production delivery, and reusable platform thinking, while providing the coaching and structure needed to grow technical depth and business understanding.
- Proves value quickly — helps frame priority problems and builds PoCs, PoVs, and MVPs using real data and workflows.
- Supports production delivery — contributes to engineering validated concepts for secure, reliable, compliant, and supportable use.
- Builds for reuse — creates components and patterns that can be adapted across therapy areas, regions, teams, and use cases.
- Improves decisions and impact — develops solutions that help Medical Affairs understand performance, identify opportunities, and act.
- Works effectively with partners — collaborates with GSK Tech strategic partners and engineering teams to deliver well-designed solutions that can be supported in production.
Key Responsibilities
Embedded Discovery, Prototyping and Value Validation
- Work with Medical Affairs teams to understand scientific and operational workflows, user needs, data constraints, and measures of value.
- Contribute to priority use cases from problem framing through PoC, PoV, and MVP using short delivery cycles and direct user feedback.
- Build prototypes with representative data and real workflows, testing feasibility, usability, data quality, and potential business value.
- Document findings and evidence to continue, pivot, or stop recommendations led by product and technical leaders.
Production Engineering and Scale
- Contribute to the transition from validated MVP to production, including design, engineering, integration, testing, security, deployment, monitoring, documentation, and support readiness.
- Build reliable, maintainable solutions that follow established GSK Digital and Tech requirements for privacy, quality, compliance, performance, resilience, and user experience.
- Develop configurable components, reusable services, data products, and patterns that support expansion across Medical Affairs teams and use cases.
- Implement product measures and production telemetry to track adoption, service performance, data quality, and opportunities for improvement.
- Investigate defects and technical debt, escalating complex decisions and balancing delivery speed with maintainability.
Medical Affairs Solutions
- Data Generation: contribute to Data Generation products that improve visibility across evidence planning, study execution, evidence generation, data quality, analysis, and reporting.
- Scientific Communications: develop Digital, AI and Tech capabilities across medical writing, publications, congress activity, content development, scientific dissemination, reach, engagement, and impact.
- Medical Information: build AI-enabled features that identify inquiry trends, knowledge gaps, response performance, content needs, and emerging scientific questions while supporting accurate and compliant operations.
- MSL Engagement: contribute to solutions that strengthen planning, engagement and measurement of scientific exchange, stakeholder engagement, field insights, content use, and follow-up.
- Cross-functional impact measurement that connect data across these domains to create trusted, dashboards, analytical/insights products, and decision-support experiences.
AI-Native Engineering
- Use approved AI coding assistants and agent-based workflows for coding, testing, review, documentation, and operational support, applying human judgement and validation throughout.
- Apply GenAI, machine learning, natural language processing, knowledge retrieval, and analytics patterns under established technical guidance when appropriate to the problem.
- Implement human-in-the-loop controls, evaluation tests, and monitoring so AI-enabled capabilities remain accurate, explainable, responsible, and fit for Medical Affairs use.
Basic Qualifications
- 3–5 years of full-stack, data, analytics, or software engineering experience, including meaningful contributions to production applications or data products.
- Experience translating defined business or user needs into working software, prototypes, or analytical solutions in collaboration with product and technical colleagues.
- Working proficiency in one or more modern programming languages or frameworks.
- Hands-on experience in several of the following: data engineering, APIs, cloud platforms, application development, automated testing, DevSecOps, observability, or production support.
- Practical exposure to GenAI patterns such as retrieval-augmented generation, prompt engineering, agents, evaluation, or responsible human oversight.
- Ability to work with business stakeholders and end users, ask effective questions, explain technical choices, and communicate progress and risks clearly.
- Awareness of security, privacy, quality, and compliance expectations; experience in a regulated or high-control environment is beneficial.
Preferred Qualifications
- Experience contributing to data products, dashboards, analytical applications, decision-support tools, or insight-generation capabilities.
- Interest in or exposure to Medical Affairs processes across data generation, scientific communications, medical information, field medical or MSL engagement, and impact measurement.
- Experience in customer engineering, solutions engineering, product engineering, consulting, or a fast-paced delivery environment.
- Examples of reusing components or patterns to improve delivery speed, quality, or consistency across more than one solution.
Education
Bachelor's degree in Computer Science, Software Engineering, Data Science, Analytics, Engineering, or a related field, or equivalent practical experience.
#AGTech
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Skills
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Inclusion at GSK:
As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.
Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.
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How we rate this
Senior Lead, Forward Deployed Engineer at GSK rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in forward deployed engineer jobs at this level
Pay
- Typical forward deployed engineer job
- $180k
This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, and NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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