Senior Forward Deployed Engineer, AI Studio

Career Category

Information Systems

At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission to serve patients living with serious illnesses drives all that we do.

Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas - Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions.

As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller, happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Let's do this. Let's change the world. In this vital role, you'll join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. You will be part of AI Studio leading the technical delivery of complex AI and automation solutions through discovery, solution design, build, evaluation, production deployment, early stabilization and measurable value, production deployment, early stabilization and measurable value.

You will maintain technical continuity across the lifecycle, working with business stakeholders and multidisciplinary teams to shape the simplest viable solution, coordinate execution, make delivery trade-offs, remove blockers and contribute hands-on to critical components. The role combines enterprise solution engineering, applied AI/ML, GenAI, RAG and agents, integration, evaluation, MLOps/LLMOps, security, governance and production operations. Technical accountability complements, but does not replace, explicit product, business, compliance and long-term support ownership.

• Lead discovery by clarifying the business workflow, users, intended outcome, value hypothesis, acceptance criteria, operational constraints, data readiness, integration dependencies and production implications;
• Translate complex problems into an executable solution design, delivery plan, technical work streams, estimates, milestones, dependencies, risks, acceptance criteria, release approach and support transition.
• Build, prototype, review or contribute to critical production components to prove feasibility or unblock delivery, including AI-enabled applications, RAG, bounded agents, intelligent automation, APIs and integrations.
• Define and maintain the 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 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 behaviour with explicit release thresholds.
• Coordinate production readiness through CI/CD, staged release, monitoring, logging, SLOs, rollback, recovery, runbooks and controlled deployment; support early issue triage, stabilization and transition to the operating owner.
• Communicate evidence, risks,…