Senior Forward Deployed Engineer (AI/ML), AI Studio

Career Category

Information Systems

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Job Description

CAREER LEVEL:GCF 5 – Specialist

CAREER TRACK:Individual Contributor

PRIMARY SCOPE:End-to-end technical delivery ownership of a small AI or automation solution or substantial deployment workstream

ORGANIZATION:Applied AI AI Studio

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains at the cutting edge of innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE

Role Description:

The Senior Forward Deployed Engineer offers a unique opportunity to join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. We are the Applied AI team (AI Studio). AI Studio is Amgen’s enterprise engine for turning high-value business challenges into scalable AI products. We partner with key business partners across the company to identify the right opportunities, shape them into actionable use cases, and design, build, and launch AI products responsibly. Our work spans the full lifecycle from early discovery and rapid prototyping to production deployment, reuse across the enterprise, and measurable business impact. 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.

Roles & Responsibilities:

• 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 workstreams, 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, trade-offs and status clearly; measure adoption and value and convert delivery lessons into reusable components, accelerators, standards, documentation and playbooks.

Basic Qualifications and Experience:

•  Bachelor’s/Master’s degree with 8 - 13 years of experience in Computer Science, IT or related field.

Functional Skills:

• Technical discovery, and value framing: Workflow analysis, intended-use definition, feasibility assessment, data and integration readiness, success measures, estimates, dependency mapping and technical go/no-go recommendations.

• Enterprise solution architecture and integrati…