Join our team at AMGEN Capability Center Portugal, consistently recognized among the top companies in the Best Workplaces(TM) ranking by Great Place to Work(R) in Portugal. In 2026, we were once again distinguished as one of the top Best Workplaces in the country (category 201-500 employees), reinforcing our commitment to an exceptional employee experience and workplace culture.
We are a team of over 500 talented individuals, spanning more than 30 functions and areas of expertise, and representing over 40 nationalities. Together, we bring diverse perspectives and professional backgrounds to help shape the future of healthcare through innovation and technology.
This is your opportunity to explore a world of possibilities across areas such as Data & Analytics, Digital, Technology & Innovation, Cybersecurity, R&D Operations, Global Distribution, Finance, Regulatory Affairs, General & Administrative, Human Resources, and many more.
Located in the heart of Lisbon, our AMGEN office fosters a culture of innovation, excellence, and purpose. Come thrive with us at AMGEN, supporting our mission To Serve Patients.
What we do at AMGEN matters in people's lives.
Senior Manager, Applied AI Engineering (AI Studio)
ABOUT THE ROLE
Role Description:
The Senior Manager, Forward Deployed Engineering position 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 build and lead a high-performing team of Engineers who turn complex, high-value business requests into secure, reliable, production-ready AI and automation solutions with measurable outcomes.
Through people leadership, operating discipline and cross-functional partnership, you will ensure technical continuity from validation through deployment, stabilization, support transition and reuse. You will own capacity, performance, talent, critical decisions and team outcomes for quality, reliability, adoption enablement, cost, risk and value. FDE accountability complements, but does not replace, product, business, data, compliance, formal approval or long-term support ownership.
Roles & Responsibilities:
-
Play the dual role of Product Owner/Architect of one of the AI-Studio delivery teams and Practice lead for Forward Deployed Engineering.
-
Build an inclusive, accountable team; recruit, onboard, coach, manage performance, develop careers, strengthen succession and create growth paths across technical discovery, solution architecture, full-stack engineering, ML/GenAI, evaluation, cloud and production operations.
-
Prioritize engagements, allocate capacity, manage workload and skills coverage, establish role clarity and delivery standards and hold individuals and teams accountable for realistic commitments, evidence quality, stakeholder outcomes and sustainable team health.
-
Develop FDE craft through discovery, architecture, prototype, design, code, evaluation, security, release and incident reviews, technical communities, mentoring and deliberate assignments that build broad enterprise delivery judgment. Build out a playbook for FDE practice to scale capabilities for AI Studio as an offering
-
Translate prioritized opportunities into engagement roadmaps, staffing plans, technical workstreams, milestones, dependencies, ownership, acceptance criteria, adoption dependencies, support models and measurable technical and business outcomes.
-
Guide technical validation and choices among conventional software, deterministic automation, ML, deep learning, GenAI, RAG, agents and human-led workflows; recommend proceed, rescope, redirect or no-go and favour the simplest safe approach that delivers value.
-
Lead multi-team delivery from discovery and feasibility through integrated architecture, implementation, evaluation, deployment, controlled rollout, stabilization and support transition; coordinate full-stack, data, ML, context engineering, testing, platform, security, Quality, GxP, compliance and business roles while preserving specialist and approval ownership.
-
Hold teams accountable for accessible human-AI experiences; coherent application, data, model, retrieval, agent and integration architecture; sound baselines, uncertainty, robustness and representative software and AI evaluation; secure interfaces, access controls, guardrails, human oversight, observability, DevSecOps and MLOps/LLMOps, SLOs, rollback, recovery, Responsible AI, privacy, validation and applicable GxP evidence.
-
Sponsor reusable architectures, accelerators, components, APIs, evaluators, standards and playbooks; use scorecards for delivery, quality, adoption, cost, risk, reuse and value, build senior stakeholder trust and reduce key-person dependency across the delivery system.
Basic Qualifications and Experience:
-
Doctorate Degree and 2 years of experience in Computer Science, IT or related field OR
-
Master’s degree with 10 - 12 years of experience in Computer Science, IT or related field OR
-
Bachelor’s degree with 12 - 14 years of experience in Computer Science, IT or related field OR
-
Diploma with 14 - 18 years of experience in Computer Science, IT or related field
Functional Skills:
-
People leadership and FDE operating systems: Hiring, onboarding, role clarity, capacity, coaching, performance, careers, succession, psychological safety, engagement staffing, technical communities, accountability and sustainable team health.
-
Technical discovery, validation, solution shaping and value: Workflow and intended-use analysis, feasibility, data and integration readiness, value hypotheses, proceed/rescope/redirect/no-go recommendations, roadmaps, acceptance criteria, adoption dependencies and measurable outcomes.
-
Integrated full-stack, data and AI architecture leadership: Human-AI experiences, applications, APIs, services, events, workflows, data and knowledge systems, ML, foundation models, RAG, agents, automation, cloud, identity, security, enterprise integration and support boundaries.
-
Delivery orchestration, evaluation and regulated readiness: Multi-disciplinary planning, milestones, dependencies, trade-offs, blocker removal, software testing, AI evaluation, release evidence, guardrails, human oversight, Responsible AI, privacy, validation, GxP and auditability.
-
Lifecycle operations, reuse and stakeholder leadership: CI/CD, infrastructure as code, SLOs, observability, staged release, rollback, incidents, recovery, capacity, FinOps, stabilization, support transition, reusable capabilities, scorecards and evidence-based executive communication.
Must-Have Skills:
-
Demonstrated direct people leadership with accountability for hiring, coaching, performance management, workload prioritization, career development, team health, inclusion, succession and talent decisions.
-
Demonstrated leadership of multiple complex production AI, automation, data or enterprise software deployments from complex request through controlled launch, early stabilization, support transition and measurable outcome.
-
Strong technical credibility across enterprise full-stack engineering, data and knowledge systems, ML/GenAI/RAG/agents, APIs and integrations, cloud, evaluation, security, governance and production operations, with sound judgment about when to engage Principal specialists.
-
Proven ability to translate complexity into coherent technical plans, allocate capacity, manage cross-team dependencies and trade-offs, communicate evidence and risk to senior stakeholders and maintain clear boundaries among FDE, product, business, control and support ownership.
Good-to-Have Skills:
-
Enterprise AI and forward-deployed delivery: Experience leading AI-enabled applications, workflow automation, Applied ML, GenAI, RAG, agentic or multimodal solutions that integrate full-stack, data, model, evaluation and operational work across multiple teams.
-
Cloud, data, platform and operational leadership: Experience with AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless or event platforms, infrastructure as code, API management, observability, MLOps/LLMOps, SLOs, incident programs, capacity planning and FinOps.
-
Advanced knowledge, agent and human-AI systems: Experience with access-aware retrieval, vector or graph stores, knowledge graphs, model or agent gateways, MCP-style integration, durable agents, automated evaluation gates, red teaming, document or vision systems and accessible review or approval experiences.
-
Reusable capability, vendor, regulated and global strategy: Experience defining platform contribution, ownership, compatibility, support, funding and deprecation; build-versus-buy, model/vendor and technology-exit decisions; and delivery in biotechnology, pharmaceutical, healthcare, GxP, validated or globally distributed environments.
Soft Skills:
-
Inclusive people leadership, coaching, performance management, talent development and the ability to create accountability with psychological safety.
-
Strategic prioritization and sound judgment when balancing user and business value, evidence, speed, quality, accessibility, security, compliance, cost, reuse, maintainability and supportability, including the courage to simplify, stop or redirect work.
-
Executive communication, stakeholder management and evidence-based resolution of ambiguity, conflict, uncertainty and cross-functional trade-offs.
-
Ability to create clarity and sustainable delivery across multidisciplinary and globally distributed teams without key-person dependency, while engaging Principal specialists and control functions at the right time.
Objects in your future are closer than they appear. Join us.
CAREERS.AMGEN.COM
EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race, colour, 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 with 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.
