[Hiring] Specialist GenAI Architect @Amgen

Role Description

Join Amgen’s Mission of Serving Patients. In this vital role, you will have an opportunity to be a hands-on architecture leader within the Applied AI – AI Productivity and Custom GPT Solutions Practice. The role defines and guides secure, scalable, reusable, and production-ready GenAI solutions that enable Amgen organizations to adopt LLM-powered assistants, agents, Custom GPTs, and AI-enabled applications.

This role translates business needs into end-to-end technical designs, establishes reference architectures and guardrails, validates critical concepts through targeted prototypes, and guides engineering teams from solution discovery through production deployment and operational handover.

Responsibilities

• 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 patterns, 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 ensure 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.

Qualifications

• 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.

Preferred Skills

• Experience with ChatGPT Enterprise, OpenAI APIs and SDKs, MCP servers and apps, ChatGPT Skills, LangChain, LangGraph, n8n, or comparable agent technologies.
• Hands-on experience with Amazon Bedrock, related agent capabilities, and other AWS AI services.
• Experience with Databricks, Unity Catalog, Vector Search, SQL Warehouses, semantic layers, or governed natural-language-to-SQL solutions.
• Working knowledge of modern web application architecture using TypeScript, React, Next.js, API-driven user experiences, automated testing, and CI/CD practices.
• Experience with responsible AI, threat modeling, AI security, model governance, GxP, computer-system validation, or other regulated technology environments.
• Relevant cloud, architecture, security, data, or AI certifications.

Benefits

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

Salary Range

105,745.10 CAD - 143,066.90 CAD