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Amgen
Amgen

Senior Forward Deployed Engineer, AI Studio

United States - Remote
1+ years exp
Full-time
Posted 3d ago
1 views
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Job Description

Career Category

Information Systems##

Job Description

Join Amgen’s Mission of Serving Patients

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.

Senior Forward Deployed Engineer, AI Studio

What you will do

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.

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.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The dynamic professional we seek is a collaborative professional with the following qualifications.

  • Basic Qualifications:
  • Doctorate Degree and 1 year of experience in Computer Science, IT or related field OR
  • Master’s degree with 8 - 10 years of experience in Computer Science, IT or related field OR
  • Bachelor’s degree with 10 - 12 years of experience in Computer Science, IT or related field OR
  • Diploma with 12 - 14 years of experience in Computer Science, IT or related field
  • Preferred Qualifications:
  • 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 integration: 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: 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.
  • Evaluation, quality and regulated delivery: Representative evidence, baselines, gold sets, error taxonomies, expert adjudication, model and retrieval quality, task success, safety, latency, reliability, failure analysis, Responsible AI, privacy, validation, auditability and GxP controls.
  • Cloud, DevSecOps and lifecycle operations: Cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged release, rollback, incidents, disaster recovery, capacity, FinOps, runbooks and MLOps/LLMOps.
  • Demonstrated end-to-end technical ownership of at least production AI, ML, software, data or automation solution that delivered a measurable enterprise outcome.
  • Strong hands-on proficiency in Python and SQL, with experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines and enterprise integrations.
  • Proven ability to turn 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 role-defining pillar—Applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps—plus credible breadth across the production lifecycle.
  • Advanced RAG, knowledge and agent systems: Hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement and adversarial testing.
  • Cloud, data and AI platforms: AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless or event-driven systems, infrastructure as code, MLflow, Airflow, Kubeflow, observability and FinOps.
  • Full-stack, workflow and automation breadth: JavaScript or TypeScript, modern web applications, API gateways, distributed workflows, process automation, document or vision capabilities and human-AI review experiences.
  • Regulated delivery and capability building: Life sciences, biotechnology, pharmaceutical, healthcare, GxP or validated-system experience; reusable frameworks, accelerators, standards, platform capabilities and mentoring.
  • Excellent critical thinking and ability to create clarity, structure and forward momentum in ambiguous situations.
  • Strong technical leadership through influence, credibility, constructive challenge and hands-on problem solving.
  • Clear communication of evidence, uncertainty, risks, trade-offs, limitations and delivery status to diverse audiences.
  • Sound judgment, ownership and resilience when balancing value, speed, quality, security, compliance, cost, maintainability and supportability across global teams.

What you can expect of us

As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.

The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.

In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:

  • 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. Refer to the Work Location Type in the job posting to see if this applies.

Apply now and make a lasting impact with the Amgen team.

careers.amgen.com

In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Application deadline

Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.

Sponsorship

Sponsorship for this role is not guaranteed.

As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

.

Salary Range

156,190.05USD -211,315.95 USD

Key Requirements & Skills

  • Doctorate Degree and 1 year of experience in Computer Science, IT or related field OR
  • Master’s degree with 8 - 10 years of experience in Computer Science, IT or related field OR
  • Bachelor’s degree with 10 - 12 years of experience in Computer Science, IT or related field OR
  • Diploma with 12 - 14 years of experience in Computer Science, IT or related field
  • 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 integration: 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: 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.
  • Evaluation, quality and regulated delivery: Representative evidence, baselines, gold sets, error taxonomies, expert adjudication, model and retrieval quality, task success, safety, latency, reliability, failure analysis, Responsible AI, privacy, validation, auditability and GxP controls.
  • Cloud, DevSecOps and lifecycle operations: Cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged release, rollback, incidents, disaster recovery, capacity, FinOps, runbooks and MLOps/LLMOps.
  • Demonstrated end-to-end technical ownership of at least production AI, ML, software, data or automation solution that delivered a measurable enterprise outcome.
  • Strong hands-on proficiency in Python and SQL, with experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines and enterprise integrations.
  • Proven ability to turn 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 role-defining pillar—Applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps—plus credible breadth across the production lifecycle.
  • Advanced RAG, knowledge and agent systems: Hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement and adversarial testing.
  • Cloud, data and AI platforms: AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless or event-driven systems, infrastructure as code, MLflow, Airflow, Kubeflow, observability and FinOps.
  • Full-stack, workflow and automation breadth: JavaScript or TypeScript, modern web applications, API gateways, distributed workflows, process automation, document or vision capabilities and human-AI review experiences.
  • Regulated delivery and capability building: Life sciences, biotechnology, pharmaceutical, healthcare, GxP or validated-system experience; reusable frameworks, accelerators, standards, platform capabilities and mentoring.
  • Excellent critical thinking and ability to create clarity, structure and forward momentum in ambiguous situations.
  • Strong technical leadership through influence, credibility, constructive challenge and hands-on problem solving.
  • Clear communication of evidence, uncertainty, risks, trade-offs, limitations and delivery status to diverse audiences.
  • Sound judgment, ownership and resilience when balancing value, speed, quality, security, compliance, cost, maintainability and supportability across global teams.

Benefits & Perks

vision capabilities and human-AI review experiences.

Frequently Asked Questions

How to apply for Senior Forward Deployed Engineer, AI Studio at Amgen?

Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.

What is the salary for this role?

Salary details will be discussed during the interview.

What experience is required?

1+ years of experience is required.

Is this position still open?

Yes, currently active and accepting applications.

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Amgen

Amgen

About | Amgen --> M Action Class" href="/"> M Action Class"> Main Menu About Overview Amgen History Mission and Values Leadership Brand Partners Amgen Foundation Awards and Accolades Therapy Areas Cardiovascular Metabolic Bone Health Inflammation Oncology How We Operate Overview Corporate Governance Business Ethics and Compliance Policies, Practices and Disclosures Science Overview Research & Development Strategy Overview Human & Disease Biology Novel Targets & Modalities Clinical Trial Optimization AI & Data Science Pipeline Scientific Advisory Boards Biosimilars Clinical Trials Overview Abou

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Senior Forward Deployed Engineer, AI Studio

Amgen · United States - Remote

Apply on Company Website