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 one 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 one 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.
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- Salary Range
- 156,190.05USD -211,315.95 USD
