GenAI Architect

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Amgen

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1980

🏥 Healthcare

🧬 Biotechnology

💊 Pharmaceuticals

💰 $28.5G Post-IPO Debt on 2022-12

Healthcare • Biotechnology • Pharmaceuticals

Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.

📋 Description

• Lead end-to- end architecture for LLM-powered assistants, agents, Custom GPTs, RAG solutions, and AI-enabled applications across experience, model, retrieval, orchestration, integration, security, cloud, deployment, and observability layers. • Translate functional and non - functional use case requirements into architecture documents, diagrams, integration patterns, data flows, security models, deployment designs, and implementation guidance. • Select appropriate pattern s, including prompt engineering, RAG, agentic orchestration, workflow automation, traditional software logic, or model customization—based on quality, risk, scalability, latency, cost, and supportability. • Architect solutions using ChatGPT Enterprise, MCP-based apps, ChatGPT Skills, enterprise APIs, Databricks, vector search, governed data sources, and approved AI platforms. • Design agentic and event-driven solutions using OpenAI SDKs, LangChain / LangGraph, n8n, APIs, webhooks, and human-in-the-loop controls. • Develop targeted proofs of concept and reference implementations to validate architecture decisions, reduce delivery risk, and accelerate engineering execution. • Guide delivery teams through implementation and ensur e delivered solutions remain aligned with approved architecture, security controls, engineering standards, and operational requirements. • Conduct solution and architecture reviews; identify technical risks, platform constraints, security gaps, data-governance concerns, and operational dependencies; and document decisions, assumptions, tradeoffs, and recommendations. • Establish reusable reference architectures, solution patterns, technical standards, guardrails, and architecture decision records for enterprise GenAI adoption. • Define non - functional requirements covering privacy, security, responsible AI, performance, scalability, observability, auditability, maintainability, and total cost of ownership. • Define safeguards for prompt injection, data leakage, unauthorized retrieval, insecure tool execution, excessive agency, secrets exposure, and inappropriate model outputs, including appropriate human oversight for high-risk actions. • Establish secure identity and access patterns using OAuth, service identities, delegated authorization, role-based access control, secrets management, least privilege, and user-level auditability. • Define evaluation, regression-testing, red-teaming, tracing, monitoring, deployment, rollback, incident-management, and operational-readiness approaches for production GenAI systems. • Evaluate emerging AI platforms and technologies and contribute to the GenAI capability roadmap by identifying platform gaps, reusable services, standard integrations, and strategic architecture improvements. • Partner with product owners, business leaders, engineering, data, platform, DevOps, cybersecurity, privacy, responsible AI, and enterprise architecture teams to move solutions from concept to production. • Facilitate architecture workshops and communicate technical options, tradeoffs, dependencies, risks, and recommendations to technical teams and senior stakeholders. • Provide technical leadership across multiple GenAI initiatives, mentor engineers and solution designers, and support architecture consultations, design clinics, and technical office hours. • Produce concise architecture documents, technical specifications, implementation guidance, runbooks, and handover materials that support long-term operational sustainability.

🎯 Requirements

• Master’s degree with 6 or more years of relevant experience in Computer Science, Information Technology, Engineering, Data Science, or a related field; or Bachelor’s degree with 8 or more years of relevant experience in Computer Science, Information Technology, Engineering, Data Science, or a related field. • 6 or more years of progressive experience in software engineering, system design, cloud architecture, or solution architecture, including at least 2 years leading end-to-end technical design or serving as a lead engineer, technical architect, or solution architect. • 2 or more years of hands-on experience architecting and delivering production GenAI applications, assistants, agents, Custom GPTs, or RAG solutions on ChatGPT Enterprise or comparable enterprise AI platforms. • Strong knowledge of GenAI solution architecture, including model selection, prompt and context design, RAG, embeddings, vector and hybrid retrieval, agent orchestration, tool integration, evaluation, guardrails, observability, and cost optimization. • Demonstrated experience defining end-to-end architectures across application, AI, data, integration, security, cloud, deployment, and operational layers. • Demonstrated experience architecting secure, scalable, and production-ready solutions on AWS, using managed AI services and cloud-native compute patterns such as AWS Lambda, Amazon ECS on AWS Fargate, and Amazon EC2, with strong knowledge of IAM, VPC networking, API Gateway, event-driven integration, observability, resiliency, and cost optimization. • Experience designing secure enterprise integrations using REST APIs, event-driven patterns, OAuth, service identities, role-based access control, secrets management, and least-privilege access. • Strong hands-on proficiency in Python and experience developing prototypes, reference implementations, APIs, evaluation utilities, or integration components for GenAI solutions. • Experience conducting architecture reviews, creating architecture artifacts, documenting decisions and tradeoffs, defining nonfunctional requirements, and guiding engineering teams through implementation. • Ability to communicate complex technical recommendations clearly to engineers, product owners, platform teams, business stakeholders, and senior leaders.

🏖️ Benefits

• Competitive and comprehensive Total Rewards Plans aligned with local industry standards