{"id":3318186,"url":"https://alion.io/job/gsk-senior-full-stack-engineer","title":"Senior, Full Stack Engineer","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":"B","score":84,"open_postings":54,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Philadelphia, United States","Durham, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":193000,"max_usd":334000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1195},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Next.js","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-02T09:59:47Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Enterprise AI (EAI) builds AI products that combine real modelling work with user-facing applications, and ships them to production. Full Stack Engineers move across data, models, platforms, APIs and interfaces in a single workflow. In our operating model, digital workers do much of the hands-on build. They generate services, APIs, interface components and tests, run evaluations and monitor what is in production. Our engineers set the architecture and standards that work is built to, and own the quality of what ships.\nEAI products and agents draw on a governed context layer that makes data, meaning, permissions and history retrievable at the moment they are needed. Full Stack Engineers build the products and agents that consume it, and decide how that context reaches users.\nThe Senior Full Stack Engineer leads the design and delivery of a significant AI product area, spanning modelling workflows and user-facing applications. The role sets the team's standards for APIs, AI integration, interfaces and observability, designs the agentic research systems that drive continuous iteration, and mentors junior and mid-level engineers.\nLeads a significant AI product area across modelling workflows, platforms and APIs and user-facing interfaces, owning architecture, quality and outcomes.\nDefines how the team builds with digital workers through the API, integration and interface standards and the review patterns their work must meet within EAI's operating model.\nDesigns agentic research systems that drive continuous experimentation, evaluation and product iteration, and raises the engineering bar by mentoring junior and mid-level engineers.\nKey Responsibilities\nTechnical Leadership & Research Practice\nSet technical direction for the product area and its modelling pipelines, defining boundaries, evaluation strategies and defensible trade-offs on performance, reliability and cost.\nDesign agentic research systems: auto-research agents that run experiments and synthesise findings, agents that monitor and improve production models, and agents that scaffold and iterate on features.\nPartner with product, design and research to shape what gets built, challenging weak ideas and communicating trade-offs clearly.\nAgent-Operated Engineering\nDefine the team's patterns for agent-generated work within EAI's operating model: what digital workers build and change on their own, which evaluation gates their work must pass, and when it needs human review.\nSet the team's AI-assisted development patterns for coding and research agents, establishing safe, effective use the team adopts.\nPlatforms & APIs\nLead the design of API layers that serve multiple consumers, defining integration contracts and non-functional requirements for the team.\nSet or improve API design standards used across the product area, and guide others on backend architecture decisions.\nLead the creation of shared infrastructure and tooling that materially reduces integration cost across multiple teams, and drive its adoption.\nAI Integration & Context\nDesign AI orchestration architectures at production scale: agent frameworks, multi-step workflows, retrieval, tool use, guardrails and integration patterns.\nDefine the team's standards for AI integration, evaluation and responsible deployment, including how the product area's products and agents draw on the governed context layer with clear permissions and provenance. Resolve production AI failure modes as they arise.\nAI-Native Experience\nLead frontend architecture for the product area, defining the UI patterns and component library the team works from.\nDrive AI interface design that achieves measurable adoption, with confidence signals, error states, provenance and human-override paths, and guide others on UX engineering quality.\nLLMOps & System Health\nLead the team's LLMOps and observability strategy, designing evaluation pipelines and production monitoring at scale.\nDefine standards for AI model lifecycle management, versioning and inference cost tracking across the product area.\nStandards & Mentorship\nSet engineering standards for the team, written to be followed by humans and digital workers alike, with measurable improvements in test coverage, API contract quality and deployment reliability.\nMentor junior and mid-level engineers through pairing, review and direct feedback, with visible improvement in their delivery capability.\n\nWhy You? \nBasic Qualification\nWe are seeking professionals with the following required skills and qualifications to help us achieve our goals: \nBachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience\n8+ years of combined experience across applied ML or data science and full-stack engineering, with significant time leading delivery of complex, user-facing AI products.\nExpertise across the AI product stack, including modelling and evaluation, modern frontend frameworks, backend services and cloud deployment, such as React or Next.js, Python or TypeScript, and AWS, Azure or GCP.\nExperience leading the design of API layers that serve multiple consumers, with integration contracts and non-functional requirements others build to.\nExperience designing AI orchestration at production scale: LLM integration, retrieval, tool and function calling, agent frameworks, evaluation, and cost, latency and quality trade-offs.\nExperience leading frontend architecture and LLMOps for a product area, including evaluation pipelines, production monitoring and model lifecycle management.\nExperience designing and operating agentic systems that drive continuous research or product iteration, and AI-assisted development patterns a team adopted.\nPreferred Qualification\nIf you have the following characteristics, it would be a plus: \nMaster's or PhD preferred, in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience.\nTechnical lead for one or more AI products combining modelling and full-stack delivery, from first build through to scale.\nBuilt or improved internal developer or research tooling, particularly for AI-assisted development and auto-research.\nExperience in a regulated industry, such as life sciences, where data integrity and auditability are mandatory.\nLeads the design of API layers serving multiple consumers; defines integration contracts and non-functional requirements for the team and Sets or improves API design standards used across a product area; guides others on backend architecture decisions\nDesigns AI orchestration architectures at production scale, including agent frameworks, multi-step workflows and how products draw on the governed context layer and defines team standards for AI integration, evaluation and responsible deployment; resolves production AI failure modes\n Leads frontend architecture for a product area; defines the UI patterns and component library the team works from.\nDrives AI interface design that achieves measurable adoption; guides others on UX engineering quality\nLeads the team's LLMOps and observability strategy; designs evaluation pipelines and production monitoring at scale and defines standards for AI model lifecycle management, versioning and inference cost tracking across a product area\nSets engineering standards for the team, including patterns for agent-generated work; drives measurable improvements in test coverage, API contract quality or deployment reliability.\nDesigns agentic research systems in production: auto-research, evaluation-driven improvement loops and agent-driven prototyping.\nWhat Success Looks Like\nIn the first 12 months, the person in this role will have:\nLed delivery of a significant AI product area spanning modelling and application work, owning architecture and outcomes.\nDefined the team's patterns for agent-generated work and its standards for APIs, AI integration and interfaces, with measurable improvements in quality or reliability.\nDesigned and shipped an agentic research system that measurably accelerated experimentation or product iteration.\nMentored junior and mid-level engineers who now deliver with greater capability and independence.\nLocation and Working Model \n- This role is based in the United States. \n- Flexible working options available, including hybrid arrangements depending on team needs. \n#Li-GSK\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)Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.\nWhy 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.\nIf you require an accommodation or other assistance to apply for a job at GSK, please contact the appropriate Recruitment Staff by emailing us at - \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.\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. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.\nPlease note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms...","description_format":"text","description_chars":12005,"description_truncated":true,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Prescription Drugs","Vaccines","Oncology Therapeutics","Infectious Disease Therapeutics"],"lifecycle":[{"event":"open","at":"2026-10-27T06:18:09Z"}],"visa":[],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.581,"p_room":0.9,"age_days":7,"expected_fill_days":16,"reasons":["conf:7","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-11-02T06:13:15Z"},"pay":null,"html_url":"https://alion.io/job/gsk-senior-full-stack-engineer","json_url":"https://alion.io/job/gsk-senior-full-stack-engineer.json","meta":{"generated_at":"2026-11-02T13:23:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":18192,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-03T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6649},"rest":"https://alion.io/mcp/rest/get_company?id=6649"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgsk-senior-full-stack-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fgsk-senior-full-stack-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fgsk-senior-full-stack-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/gsk-senior-full-stack-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgsk-senior-full-stack-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3318186}},{"tool":"search_jobs","arguments":{"company":"gsk.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3318186},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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