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Amgen

Makes biotech medicines for serious illnesses

Associate AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeThousand Oaks, CA, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or a diploma plus at least two years of experience in Computer Science, Engineering, Data Science, or a related field.
  • End-to-end solution architecture and integration across applications, APIs, services, data and knowledge flows, models, retrieval, agents, workflows, persistence, identity, security zones, enterprise systems, and support boundaries.
  • Production Python and SQL, classical machine learning and natural language processing awareness, foundation-model integration, prompt and context management, retrieval-augmented generation, structured output, provenance, citations, bounded tool use, permissions, recovery, and human control.
  • Cloud-native services, containers, continuous integration and continuous delivery, infrastructure as code, versioning, observability, service-level objectives, staged release, rollback, incident response, disaster recovery, capacity, financial operations, runbooks, and machine learning/model lifecycle operations.
  • Hands-on proficiency in Python and SQL, with experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines, and enterprise integrations.
  • Ability to turn complex business problems into technical designs, delivery plans, acceptance criteria, and production-readiness evidence while coordinating multidisciplinary teams.
  • Advanced capability in at least one role-defining pillar: applied AI/machine learning, generative AI/retrieval-augmented generation/agents, full-stack and integration engineering, or AI platform/model lifecycle operations, with breadth across the production lifecycle.
  • Advanced retrieval-augmented generation, knowledge and agent systems, including hybrid or graph retrieval, knowledge graphs, source verification, Model Context Protocol-style integration, durable or multi-agent workflows, policy enforcement, and adversarial testing.

Responsibilities

  • Clarify business workflows, users, intended outcomes, value hypotheses, acceptance criteria, operational constraints, data readiness, integration dependencies, and production implications.
  • Translate complex problems into solution designs, delivery plans, technical workstreams, estimates, milestones, dependencies, risks, acceptance criteria, release approaches, and support transitions.
  • Build, prototype, review, or contribute to critical production components to prove feasibility or unblock delivery, including AI-enabled applications, retrieval-augmented generation, bounded agents, intelligent automation, APIs, and integrations.
  • Define and maintain integrated architecture across applications, workflows, data and knowledge pipelines, models, retrieval, agents, APIs, enterprise integrations, identity, access controls, observability, and human review.
  • Coordinate delivery across full-stack software and AI engineering, data science, machine learning and context engineering, testing, platform, security, compliance, and business roles.
  • Establish integrated testing, AI evaluation, and governance covering functional, performance, security, data, model, retrieval, generation, tool-use, human-oversight, and operational behavior, with explicit release thresholds.
  • Coordinate production readiness through continuous integration and delivery, staged release, monitoring, logging, service-level objectives, rollback, recovery, runbooks, and controlled deployment; support early issue triage, stabilization, and transition to the operating owner.
  • Communicate evidence, risks, trade-offs, and status; measure adoption and value; and turn delivery lessons into reusable components, accelerators, standards, documentation, and playbooks.

Desired Qualifications

  • Experience with Databricks, AWS, Spark, large language models, and agentic development solutions.
  • Experience in life sciences, healthcare, payor, or pharmaceutical environments.

About the Company

Amgen

Makes biotech medicines for serious illnesses

Amgen develops and makes biologic medicines, which are drugs built from proteins and antibodies grown in living cells, for serious conditions such as heart disease, cancer, and bone loss. Its anemia drug Epogen, approved in 1989, became one of the biotechnology industry's first blockbuster medicines. Amgen grows these drugs in large tanks called bioreactors, and its products include the cholesterol drug Repatha, the bone-building drug Evenity, and the severe asthma drug Tezspire. It earns money by selling these medicines, mostly through large drug wholesalers that supply hospitals and pharmacies. Amgen was founded in 1980 and is based in Thousand Oaks, California.

Company size
10,001+
Company stage
IPO
Headquarters
Thousand Oaks, CA
Founded
1980

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