Senior Forward Deployed Engineer, AI Studio

🕒 August 5

🇺🇸 United States – Remote

💵 $156.2k - $211.3k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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Amgen

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1980

🏥 Healthcare

🧬 Biotechnology

💊 Pharmaceuticals

💰 $28.5G Post-IPO Debt on 2022-12

Healthcare • Biotechnology • Pharmaceuticals

Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.

📋 Description

• Lead discovery by clarifying business workflows, users, intended outcomes, value hypotheses, acceptance criteria, constraints, data readiness, dependencies and production implications • Translate complex problems into executable solution designs, delivery plans, technical workstreams, estimates, milestones, risks, acceptance criteria, release approaches and support transitions • Build, prototype, review or contribute to critical production components 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 engineering, data science, ML, testing, platform, security, compliance and business teams • Establish integrated testing, AI evaluation and governance 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

🎯 Requirements

• Doctorate degree and 1 year of experience in Computer Science, IT or related field, OR Master’s degree with 8–10 years of experience, OR Bachelor’s degree with 10–12 years of experience, OR Diploma with 12–14 years of experience • Technical discovery, workflow analysis, feasibility assessment, data and integration readiness, success measures, estimates and dependency mapping • Enterprise solution architecture and integration across applications, APIs, services, data, models, retrieval, agents, workflows, identity, security and enterprise systems • Production Python and SQL • Classical ML and NLP awareness • Foundation-model integration, prompt and context management, RAG, structured output, provenance, citations, bounded tool use, permissions, recovery and human control • Experience with evaluation, quality, safety, privacy, validation, auditability, Responsible AI and GxP controls • Cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged release, rollback, incident response, disaster recovery, capacity, FinOps, runbooks and MLOps/LLMOps • End-to-end technical ownership of at least one production AI, ML, software, data or automation solution delivering a measurable enterprise outcome • Experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines and enterprise integrations • Ability to turn complex business problems into technical designs, executable delivery plans, acceptance criteria and production-readiness evidence • Advanced capability in at least one of Applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps • Advanced RAG, knowledge and agent systems, including hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement and adversarial testing • Experience with AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless or event-driven systems, infrastructure as code, MLflow, Airflow, Kubeflow, observability and FinOps • Experience with JavaScript or TypeScript, modern web applications, API gateways, distributed workflows, process automation, document or vision capabilities and human-AI review experiences • Life sciences, biotechnology, pharmaceutical, healthcare, GxP or validated-system experience is valued • Strong critical thinking, technical leadership, communication, judgment, ownership and resilience

🏖️ Benefits

• Comprehensive employee benefits package • Retirement and Savings Plan with generous company contributions • Group medical, dental and vision coverage • Life and disability insurance • Flexible spending accounts • Discretionary annual bonus program • Stock-based long-term incentives • Award-winning time-off plans • Flexible work models where possible • Career development opportunities • Work/life balance support