Senior Manager, Applied AI Engineering (AI Studio)

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 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 peoples 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 Amgens 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
• Masters degree with 10 - 12 years of experience in Computer Science IT or related field OR
• Bachelors 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.

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EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your racecolour 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 toparticipatein the job application or interview process to perform essential job functions and to receive other benefits and privileges of employment.

Salary Range