{"id":3485984,"url":"https://alion.io/job/gsk-senior-forward-deployed-engineer-digital-twin-optimization","title":"Senior, Forward Deployed Engineer (Digital Twin & Optimization)","company":{"id":6649,"name":"GSK","domain":"gsk.com","url":"https://alion.io/company/gsk","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":86,"open_postings":58,"ghost_share":0,"stale_share":0.759,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom","Stevenage, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":153000,"max_usd":278000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":34},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Databricks","optional":false},{"name":"Digital Twin","optional":false},{"name":"JavaScript","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"GDPR","optional":true}],"status":"live","first_seen_at":"2026-10-27T00:00:00Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-31T19:46:48Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Senior, Forward Deployed Engineer (Digital Twin & Optimization)\nAbout GSK Enterprise AI\nEnterprise AI is GSK’s centre of gravity for applied artificial intelligence. We pair forward deployed engineers and full-stack engineers with scientific, clinical, and business teams to build AI products that get used - not pilots that get archived. We work fast, ship in production, and measure ourselves on outcomes that matter to patients.\nGSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. We are committed to building a diverse and inclusive team - we welcome candidates from all backgrounds and underrepresented groups in technology, science, and pharma.\nPosition Summary\nGSK’s Enterprise AI team builds AI solutions that prove value fast and scale to production. The Forward Deployed Engineer (FDE) is the engineer GSK sends in to find out whether an AI idea will work - embedded with business unit (BU) teams, proving ideas through proofs of concept (PoCs), proofs of value (PoVs), and minimum viable products (MVPs) at a days-to-weeks cadence, then handing the proven solution off to the Sr. Solutions Engineer for scale-up. The pattern is proven by AI-native companies - Anthropic, Palantir, OpenAI - and this role brings that model to GSK.\nThis specific role sites in the Chemical Manufacturing & Control (CMC) area. This is the GSK function that turns a validated molecule into a reliably manufactured, quality-assured medicine; its mission is to get safe, effective, consistently manufactured medicines to patients, faster. Its current mission is to double New Product Introductions (NPIs).\nAs a Senior Forward Deployed Engineer, you’ll be embedded in a team shaping how AI transforms GSK’s process development around the world. Most prototyping work is AI-augmented: AI coding assistants and multi-agent workflows handle the bulk of routine coding, freeing the FDE to focus on framing, judgement, and validation. The role works directly inside the customer’s business and emerges with working software and a defensible value hypothesis, not slideware. The FDE does not carry use cases through to long-term operations and partner with the Sr. Solutions Engineer is part of the role.\nThis role will build in-silico process models and digital twin capabilities to foster the process development of molecules. You will work on foundation models, platform fitness models and tech transfer twins, plus scenario planning and scheduling optimization. You will still build models yourself, with a platform mindset: platform models and end-to-end solutions, not point solutions. Process modelers remain the process experts and co-own the models. You bring the AI modeling and engineering that makes building, deploying and using models 10x more efficient. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you.\nKey Responsibilities\nThis role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:\nPoC / PoV / MVP Delivery\nTake ownership of high-priority BU use cases from problem framing through to a working prototype, at days-to-weeks cadence, and form a defensible view on whether each should progress.\nShip first production versions directly for use cases where the path is clear - before the Sr. Solutions Engineer takes them forward to scale.\nAI-Native Engineering\nOperate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery - selecting the right level of automation for each engagement.\nUse AI coding assistants as the default mode of building; provide judgement, course correction, and validation.\nCustomer Embedding & Handoff\nEmbed with BU teams - attend standups, understand the domain, prototype against real data and real workflows.\nPackage proven use cases cleanly for the Sr. Solutions Engineer - working code, architecture rationale, open risks, and scaling concerns.\nGovernance, Standards & Coaching\nBegin Code Orange, Responsible AI, and Accountability Report conversations during prototyping - so the productionisation team does not inherit governance debt.\nContribute reusable agents, prompt templates, and reference architectures to the organisation’s pattern library after each engagement.\nForm and defend kill/continue recommendations at the end of each engagement - presenting clearly to BU and Enterprise AI leadership.\nCoach BU engineers on AI-augmented ways of working while embedded, building BU capability alongside delivery outcomes.\nWhy You!\nWe are seeking professionals with the following required skills and qualifications to help us achieve our goals:\nStrong full-stack or AI/ML engineering experience, including production deployments.\nStrong proficiency in Python and at least one of TypeScript/JavaScript, Go, or similar.\nStrong awareness of the main process modeling approaches (mechanistic and first-principles models, hybrid models, data-driven and ML models, and process simulation), enough to work with process modelers, understand what each approach needs, and spot where AI can make it 10x more efficient. Deep experience in building mechanistic models is not expected.\nStrong AI modeling skills, including model identification: identifying, selecting and calibrating the right model structure from process data, for example with surrogate models, AutoML and agents that assist modelers.\nProven ability, as a forward deployed engineer, to take a digital twin or optimization MVP end to end, from problem framing to a working, deployed and commercial-ready solution with the scientists and modelers. This role does not own an ML engineering platform.\nStrong experience in optimization and scenario planning: linear and mixed-integer programming, constraint solvers, scheduling optimization, and simulation-based what-if analysis.\nHands-on experience with GenAI patterns (agents, multi-agent orchestration, evaluation) and enough machine learning operations (MLOps) and model serving to ship an MVP to production.\nDaily use of AI coding agents (Claude Code, GitHub Copilot, Databricks AI Assistant) as the primary mode of development.\nPreferred Experience\nPrior experience as a Forward Deployed Engineer at an AI-native company (Anthropic, Palantir, OpenAI, or similar), or as a Customer Engineer / Solutions Architect at a hyperscaler.\nExperience with digital twins, surrogate or foundation models, and platform or fitness models for pharmaceutical drug substance or drug product processes.\nExperience partnering with data analytics, data science, or process science teams to turn analytical models into shared, reusable products.\nExperience in regulated industries (pharma, healthcare, financial services) and familiarity with good practice regulations (GxP), General Data Protection Regulation (GDPR), and Sarbanes-Oxley (SOX).\nTrack record of contributing reusable engineering patterns back to a broader team.\nEducation\nBachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience. Master’s degree in Computer Science or related field is advantageous.\nReady to apply? \n If this role excites you and matches your experience, we would love to hear from you. Please submit your application and a short note telling us why you want to join and what you would bring to this role. We look forward to hearing from you. If you need adjustments during the process, tell us and we will support you.\n(Please take a personal copy of the Job Description, as this will not be available online post closure of the advert)\nClosing Date: 10th November 2026\nWorking Pattern\nThis is a UK based hybrid role, with a min of 2/3 days a week onsite. Fully remote working is not available.\nLocations:\n1) HQ Central London or\n2) Stevenage - This role can be temporarily be based at Stevenage location. However, the Company plans to relocate its offices to Ware, UK. The location of this role will therefore subsequently change to Ware, UK in accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.”\nWhat we value\nYou are practical, inclusive and open to feedback. You bring technical understanding and strong empathy for users. You work in active voice and keep communication simple. You support colleagues and help teams make confident, evidence-based decisions. You want to grow your product and security skills while delivering outcomes that matter.\nWhat you will gain\nYou will join a supportive team that values clear communication and practical problem solving. You will have access to learning and development to grow both technical and leadership skills. Your work will support technology that enables critical work across the company and helps improve healthcare outcomes.\nSkills\nAI Frameworks, Algorithm Optimization, Artificial Neural Networks (ANNS), Computer Programming, Deep Learning, Feature Engineering, Google Cloud Platform (GCP) for Machine Learning, Machine Learning Algorithms, Machine Learning Operations, Microsoft Azure Data and AI, ML Frameworks, Model Evaluation, Model Training, Model Validation, Performance Optimizations, Software Development Life Cycle (SDLC)Why GSK?\nUniting science, technology and talent to get ahead of disease together.\nGSK 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.\nPeople 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.\nGSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.\nWe believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.\nShould you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at  where you can also request a call.\nPlease note should your enquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive\nImportant notice to Employment businesses/ Agencies\nGSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. 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