Associate AI Engineer, OI&A

The Associate AI Engineer within Amgen’s OI&A organization will deliver end-to-end AI solutions spanning data science, software engineering, and GenAI for enterprise functions. The role focuses on integrated solution engineering across AI/ML, RAG and agents, MLOps/LLMOps, evaluation and governance, and production operations.

Location and Work Model

Thousand Oaks, CA (hybrid)

Salary

USD 81,466 - 110,219 per year

Role Summary

In this position, you will lead discovery and translate complex business needs into executable solution designs and delivery plans. Responsibilities include building and reviewing critical production components, defining integrated architecture across workflows and data pipelines, and coordinating full-stack AI engineering efforts from testing and evaluation through deployment and stabilization.

Responsibilities

• Lead discovery by clarifying business workflow, users, intended outcome, value hypothesis, acceptance criteria, operational constraints, data readiness, integration dependencies, and production implications.
• Convert complex problems into executable solution design, delivery plans, technical workstreams, estimates, milestones, dependencies, risks, acceptance criteria, release approach, and support transition.
• Build, prototype, review, or contribute to critical production components to demonstrate feasibility or unblock delivery, including AI-enabled applications, RAG, 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.
• Orchestrate delivery across full-stack software and AI engineering, data science, ML 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 CI/CD, staged release, monitoring, logging, SLOs, rollback, recovery, runbooks, and controlled deployment, including early issue triage and transition to the operating owner.
• Communicate evidence, risks, trade-offs, and status clearly; measure adoption and value; and convert delivery lessons into reusable components, accelerators, standards, documentation, and playbooks.

Minimum Qualifications

• 2+ years of experience
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field OR a diploma with 2+ years of experience in Computer Science, Engineering, Data Science, or related field

Requirements

• Enterprise solution architecture and integration experience, including end-to-end design across applications, APIs, services, data and knowledge flows, models, retrieval, agents, workflows, persistence, identity, security zones, enterprise systems, and support boundaries.
• Applied AI/ML and GenAI engineering proficiency, including production Python and SQL, awareness of classical ML and NLP, and experience with foundation-model integration, prompt and context management, RAG, structured output, provenance and citations, bounded tool use, permissions, recovery, and human control.
• Cloud, DevSecOps, and lifecycle operations experience, including cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged release, rollback, incidents, disaster recovery, capacity, FinOps, runbooks, and MLOps/LLMOps.
• Strong 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 translate complex business problems into coherent technical designs, executable delivery plans, acceptance criteria, and production-readiness evidence while coordinating multidisciplinary teams.
• Advanced capability in at least one role-defining pillar: Applied AI/ML; GenAI/RAG/agents; full-stack and integration engineering; or AI platform/MLOps, with credible breadth across the production lifecycle.
• Advanced RAG, knowledge, and agent systems experience, including hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement, and adversarial testing.
• Experience with Databricks, AWS, Spark, LLMs, and agentic development solutions is a plus.
• Experience in life sciences, healthcare, payor, or pharmaceutical environments will be factored in.
• Self-starter mindset, demonstrating critical thinking, sound judgment, ownership, and resilience to navigate ambiguity, create clarity and momentum, and deliver business results with minimal oversight, including credible hands-on technical leadership through influence and constructive challenge, and clear communication of evidence, uncertainty, risks, trade-offs, limitations, and delivery status while balancing value, speed, quality, security, and maintainability.

Technologies

• Python
• SQL
• Databricks
• AWS
• Spark
• LLMs
• CI/CD
• Infrastructure as code
• MLOps/LLMOps

What You Will Do

• Deliver advanced data science, software engineering, and GenAI solutions enabling commercial and non-commercial functions across the enterprise.
• Maintain technical continuity across the lifecycle by working with business stakeholders and multidisciplinary teams to shape the simplest viable solution, coordinate execution, manage delivery trade-offs, remove blockers, and contribute hands-on to critical components.
• Own the integration of enterprise solution engineering with applied AI/ML, GenAI, RAG and agents, integration, evaluation, MLOps/LLMOps, security, governance, and production operations.
• Provide technical accountability that complements explicit product, business, compliance, and long-term support ownership.

Employee Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan.
• Stock-based long-term incentives.
• Award-winning time-off plans.
• Flexible work models where possible.

What You Can Expect of Us

Amgen supports your journey with competitive benefits and a collaborative culture. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is provided, and actual salary will vary based on relevant skills, experience, and qualifications.