Specialist Software Engineer (Full Stack)
Career Category
Information SystemsJob Description
CAREER LEVEL: GCF 5 - Specialist
CAREER TRACK: Individual Contributor
PRIMARY SCOPE: End-to-end ownership of a small full-stack AI product orsubstantialtechnical workstream
ORGANIZATION: Applied AI | AI Studio
ABOUT AMGEN
Amgen harnesses the best of biology and technology to fight the world’s toughest diseases and make people’s lives easier,fullerand longer. We discover, develop,manufactureand deliver innovative medicines to help millions of patients. Amgen helpedestablishthe biotechnology industry more than 40 years ago andremainsat thecutting edgeof innovation, using technology and human genetic data to push beyond what is known today.
ABOUT THE ROLE
Role Description:
TheSenior Full-Stack Software Engineeroffers a unique opportunity to join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. We are the Applied AI team (AI Studio). AI Studio is Amgen’s enterprise engine for turning high-value business challenges into scalable AI products. We partner with key business partners across the company toidentifythe right opportunities, shape them into actionable use cases, and design, build, and launch AI products responsibly. Our work spans the full lifecycle-from early discovery and rapid prototyping to production deployment, reuse across the enterprise, and measurable business impact.You will define and own a small AI product or substantial application workstream from problem framing through architecture, implementation, launch, stabilization, support transition,adoptionand measurable outcome.
You will remain hands-on while leading engineering decisions that turncomplexbusiness needs into secure, accessible,reliableand reusable products spanning user experience, APIs, distributed services, data and integrations, automation, ML, GenAI, RAG, boundedagentsand human review. Within Applied AI, AI Studio turns prioritized business demand into governed, reusable AI assets with accountable ownership and measurable value across software, data, automation, machine learning, Generative AI, RAG, bounded agents, evaluation,observabilityand lifecycle operations.
Roles & Responsibilities:
Define the user, workflow, intended use, baseline, acceptance criteria, accessibility needs, adoption path, operating owner, valuehypothesisand measurable technical and business outcomes.
Map rules, handoffs, exceptions, datadependenciesand human decision points before selecting conventional software, automation, ML, GenAI, RAG,agentsor a manual approach.
Lead sprint and release planning, estimates, capacity, dependencies, MVP and phased roadmaps, explicit assumptions, total cost of ownership and support transition.
Own production architecture across human-AI experience, frontend, API gateway, backend services, persistence, events, integrations, data/knowledge flows, AI capabilities, securityzonesand human review.
Lead responsive frontend and backend delivery using modern JavaScript/TypeScript and Python, Node.js, Java or C#, with stable contracts, asynchronous workflows, retries, idempotency, compensation, ratelimitsand graceful degradation.
Integrate model services, LLMs, RAG, search, agents, BI and deterministic automation with access-aware data, validation, representative evaluation, human control,feedbackand traceable evidence.
Establish risk-based testing, AI evaluation, CI/CD, policy gates, infrastructure as code, staged release, SLOs, telemetry, rollback, incident response, disaster recovery, capacity, cost,runbooksand support ownership.
Coordinate governance andGxPcontrols, create reusable components and playbooks, lead root-cause analysis, measure adoption and value, mentor engineers and improve delivery practices.
Basic Qualifications and Experience:
- Bachelor’s/Master’sdegree with 8 - 13 years of experience in Computer Science,ITor related field.
Functional Skills:
End-to-end full-stack and human-AI engineering: User journeys, accessible frontend architecture, state, forms, secure sessions, streaming, review, correction, approval, uncertainty, feedback,telemetryand recoverable failure.
Backend, API,dataand distributed-systems architecture: Services, events, workflows, persistence, caches, queues, transactions, retries, idempotency, compensation, multi-tenancy, consistency, resilience, contracts, datamodelsand enterprise integrations.
AI-enabled applications and automation: Production integration of predictive ML, foundation models, embeddings, vector/graph retrieval, RAG, structured output, bounded agents, document/vision capabilities, BI and deterministic workflows.
Testing, cloud,DevSecOpsand reliability: Representative testing and AI evaluation, repository governance, architecture decisions, CI/CD, infrastructure as code, quality gates, staged release, SLOs, observability, incidents, rollback, disasterrecoveryand FinOps.
Security, ResponsibleAIand regulated delivery: Identity, authorization, least privilege, tenant isolation, secrets, OWASP, supply-chain controls, privacy, threatmodeling, prompt/tool safeguards, validation, auditability,accessibilityandGxPevidence.
Must-Have Skills:
Demonstrated end-to-end ownership of at least one production full-stack application, digital product,automationor AI-enabled system that delivered a measurable outcome.
Strong hands-onproficiencyin JavaScript or TypeScript, at least one backend language such as Python, Java, C# or Node.js, and SQL, with experience designing production services.
Ability to lead application and integration architecture, delivery, release,operationsand support while partnering with ML specialists for deeper model, RAG, agent andMLOpsdecisions.
Good-to-Have Skills:
Advanced frontend and human-AI platforms: Experience with Next.js or comparable rendering patterns, design systems, micro-frontends where justified,multimodalor collaborative interfaces, advancedaccessibilityand safe agent approval experiences.
Distributed and enterprise integration: Experience with Kafka or equivalent event platforms, durable workflows, outbox or saga patterns, stream processing, service mesh, APIgatewaysand large-scale integration architecture.
Advanced AI and automation engineering: Experience with vector or graph databases, graph or multimodal retrieval, model and agent gateways, MCP-style tool integration, durable agents, agent evaluation, process mining, UiPath or n8n.
Cloud,platformand developer experience: Experience with AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless services, infrastructure as code,OpenTelemetry, policy as code or internal developer platforms.
Regulated systems and technical breadth: Experience deliveringGxP-relevant,validated, pharmaceutical,healthcareor other high-impact systems and evaluating emerging technologies pragmatically.
Soft Skills:
Product thinking and ability to connect architecture and delivery decisions to measurable user,workflowand business value.
Strong technical leadership, mentoring and ownership whileremaininghands-on.
Excellent analytical judgment, troubleshooting and clear communication of evidence,limitationsand trade-offs.
Cross-functional leadership with product, business, UX, architecture, ML,platformand control functions.
Pragmatism, resilience and continuous improvement through incidents, feedback,reuseand measured outcomes.
EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race,color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
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