Senior Forward Deployed Engineer, AI Studio

Role

Senior Forward Deployed Engineer in Amgen’s AI Studio responsible for leading technical delivery of complex AI and automation solutions across the full lifecycle: discovery, solution design, prototyping, build, evaluation, production deployment, early stabilization and measurable value. The role maintains technical continuity across stakeholders and multidisciplinary teams and balances hands-on contribution with orchestration and technical accountability.

Key Responsibilities

• Lead discovery: clarify business workflows, users, intended outcomes, value hypotheses, acceptance criteria, operational constraints, data readiness and integration dependencies.
• Translate problems into executable solution designs, delivery plans, milestones, technical workstreams, estimates, dependencies, risks and acceptance criteria.
• Build, prototype or contribute to production components to prove feasibility, including AI-enabled applications, RAG, bounded agents, automation, APIs and integrations.
• Define and maintain integrated architecture across applications, workflows, data and knowledge pipelines, models, retrieval, agents, APIs, enterprise integrations, identity and observability.
• Orchestrate delivery across full-stack engineering, data science, ML/context engineering, testing, platform, security, compliance and business roles.
• Establish integrated testing, AI evaluation and governance (functional, performance, security, data, model, retrieval, generation, tool-use, human oversight) with explicit release thresholds.
• Coordinate production readiness via CI/CD, staged release, monitoring, logging, SLOs, rollback/recovery, runbooks and controlled deployment; support early issue triage and transition to operating owners.
• Communicate evidence, risks, trade-offs and status; measure adoption and value; convert lessons into reusable components, accelerators, standards and playbooks.

Requirements

Basic Qualifications

• Doctorate with 1 year experience in Computer Science/IT or related field OR
• Master’s degree with 8–10 years experience OR
• Bachelor’s degree with 10–12 years experience OR
• Diploma with 12–14 years experience

Preferred Qualifications / Experience

• Technical discovery and value framing: workflow analysis, feasibility assessment, data/integration readiness and success measures.
• Enterprise solution architecture and integration across applications, APIs, services, data/knowledge flows, models, retrieval and agents.
• Applied AI/ML and GenAI engineering: production Python and SQL; foundation-model integration; prompt/context management; RAG; structured output; provenance and human control.
• Evaluation, quality and regulated delivery: baselines, gold sets, error taxonomies, model/retrieval quality, safety, latency, reliability, auditability and GxP controls.
• Cloud, DevSecOps and lifecycle ops: cloud-native services, containers, CI/CD, IaC, versioning, observability, SLOs, staged release, rollback, incidents, disaster recovery, FinOps, runbooks and MLOps/LLMOps.
• Demonstrated end-to-end technical ownership of production AI/ML/software/data or automation delivering measurable enterprise outcomes.
• Strong hands-on proficiency in Python and SQL and experience with production software, APIs, services, data flows and enterprise integrations.
• Advanced capability in at least one pillar: Applied AI/ML, GenAI/RAG/agents, full-stack/integration engineering, or AI platform/MLOps, with credible breadth across the production lifecycle.
• Experience with advanced RAG/knowledge/agent systems, hybrid/graph retrieval, knowledge graphs, source verification, multi-agent workflows and adversarial testing.
• Experience with cloud/data/AI platforms and orchestration (AWS, Bedrock/SageMaker, Databricks, Spark, Kubernetes, serverless, MLflow, Airflow, Kubeflow).
• Full-stack breadth including JavaScript/TypeScript, modern web apps, API gateways, distributed workflows, process automation and human-AI review experiences.
• Regulated delivery experience in life sciences/biotech/pharma/healthcare (GxP, validated systems) and mentoring/capability building.
• Strong critical thinking, communication, technical leadership, judgment, ownership and resilience in ambiguous, cross-functional environments.

Compensation & Benefits (summary)

• Posted U.S. salary range: 156,190.05 USD – 211,315.95 USD
• Comprehensive benefits including retirement and savings with company contributions, group medical/dental/vision, life and disability insurance, flexible spending accounts, discretionary annual bonus, stock-based long-term incentives, award-winning time-off plans and flexible work models where possible.