Sr Associate Software Engineer, AI Studio (Full Stack)

Career Category Information Systems Job Description CAREER LEVEL: GCF 4 – Senior Associate CAREER TRACK: Individual Contributor PRIMARY SCOPE: Independent ownership of defined full-stack production components and vertical slices 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, fuller and longer.

We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains at the cutting edge of innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE Role Description: The Full-Stack Software Engineer role offers 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 to identify the 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 independently own defined production components and vertical slices within enterprise AI applications and automation products. You will translate well-scoped requirements into reliable software, diagnose moderately complex issues across layers, connect component measures to user and workflow outcomes and coordinate with adjacent teams so the component is secure, accessible, supportable and production ready.

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, observability and lifecycle operations.

Roles & Responsibilities: Define the component boundary with product, UX, business, domain, architecture and engineering partners; clarify intended use, acceptance criteria, non-functional requirements, user outcome, support expectations and estimates.

Design and implement accessible, responsive UI components with clear state, secure sessions, loading, error, empty, streaming, review and approval patterns using modern JavaScript or TypeScript frameworks. Build APIs, services, background jobs, data models, queries, migrations, queues, events and integrations using Python, Node.js, Java or C#, SQL/NoSQL, versioned contracts, validation, authorization, retries and useful failure semantics.

Integrate approved model inference, LLMs, embeddings, vector search, RAG, structured output, agent tools, BI or workflow automation with input/output validation, human control and component-level evaluation. Implement layered unit, integration, API, contract, UI, accessibility, performance, security, data and AI-evaluation tests and use evidence to diagnose moderate cross-layer failures.

Use cloud services, containers, CI/CD, infrastructure as code where appropriate, feature flags, backward-compatible deployment, monitoring, rollback and incident practices. Define and maintain indicators for availability, latency, errors, frontend behaviour, database performance, data freshness, AI quality, user experience, operating cost and support health.

Apply identity, least privilege, OWASP, privacy, Responsible AI, accessibility, validation, traceability and GxP controls; contribute reusable components and guide Associate engineers on familiar work. Basic Qualifications and Experience: Bachler’s/Master’s degree and 5 to 9 years of Computer Science, IT or related field experience.

Functional Skills: Full-stack product engineering: Independent design, implementation, diagnosis and maintenance of a coherent frontend-to-backend production component or vertical slice. Backend, API, data and distributed systems: Versioned contracts, validation, authentication and authorization, caching, concurrency, queues, events, transactions, retries, idempotency, observability, persistence and schema evolution.

AI-enabled applications and automation: Integration of predictive models, LLMs, embeddings, vector or hybrid search, RAG, structured output, tool-using agents, BI and deterministic workflows with human control. Testing, cloud and lifecycle reliability: Layered testing, source-control discipline, technical documentation, containers, CI/CD, configuration, versioning, monitoring, rollback, incident response, root-cause analysis and support.

Security, Responsible AI and GxP: OAuth/OIDC, role-based access, least privilege, secrets, OWASP, privacy, threat awareness, prompt-injection safeguards, auditability, accessibility, validation and quality evidence. Must-Have Skills: Demonstrated ownership of at least one production frontend, backend, API, data, integration, automation or AI-enabled component.

Strong hands-on proficiency in JavaScript or TypeScript, at least one backend language such as Python, Java, C# or Node.js, and SQL. Ability to design, build, release, monitor, diagnose and maintain a defined production slice with limited guidance.

Good-to-Have Skills: Advanced frontend engineering: Experience with Next.js rendering patterns, reusable design systems, browser telemetry, frontend performance, complex data-intensive interfaces or accessible human-AI review workflows. Distributed services and integration: Experience with GraphQL, WebSocket, Kafka or other event platforms, durable workflows, outbox or saga patterns, stream processing, API gateways, graph/vector stores or complex integrations.

AI and intelligent automation: Experience with scikit-learn, PyTorch, TensorFlow, Hugging Face, model-serving APIs, RAG evaluation, agent orchestration, document intelligence, computer vision, BI or automation. Cloud and observability: Experience with AWS, Databricks, Kubernetes, serverless services, infrastructure as code, OpenTelemetry, Prometheus, Grafana, Splunk, CloudWatch or feature management.

Regulated delivery: Experience in healthcare, life sciences, GxP, validated systems or another regulated environment. Soft Skills: Independent ownership, sound technical judgment and disciplined production follow-through. Strong analytical and troubleshooting skills across frontend, API, data, integration and AI layers.

Clear communication of design decisions, estimates, evidence, trade-offs, risks and support implications. Effective collaboration with product, UX, business, architecture, ML, platform, security, quality and operations teams. Ability to guide junior engineers and improve reusable engineering practices.

EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, colour, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. .