Required skills
- AWS
- Databricks
- Data Engineering
- Business Intelligence
- Agent Design
- Multi-Agent Orchestration
- Power Apps
- Copilot Studio
- Program Management
- Stakeholder Management
- Enterprise Architecture
- Generative AI
Nice to have:AWS Data AnalyticsAWS CertificationDatabricks CertificationLarge Language ModelsGxPProduct ManagementBusiness Intelligence DevelopmentBig DataData IntelligenceMicrosoft Business Intelligence
Languages: English
Job description
Project overview
Required Skills & Experience
Technical
Domain
Delivery & Leadership
Behavioural
Desirable
Success Measures
- Data & Cloud: Strong expertise in AWS, Databricks, data engineering and BI.
- Agentic/Enterprise AI: Strong knowledge of agent design, multi-agent orchestration, routing, evaluation frameworks and guardrails.
- Responsible AI: Practical experience applying validation, explainability, security, monitoring and documentation standards.
- Power Platform: Working knowledge of Power Apps and Copilot Studio, with willingness to prototype and perform hands-on technical work.
- Good understanding of Commercial Pharma data and processes (eg sales and marketing analytics, field force, market access, patient and brand data).
- Proven experience running large, multi-workstream programs with onsite/offshore delivery models.
- Experience leading governance forums and reporting to senior business and technology stakeholders.
- Track record of owning delivery through to production with measurable business outcomes.
- Experience working with enterprise architecture, security and platform teams, including ARB processes.
- Credible, hands-on technologist who can challenge engineering decisions and also explain trade-offs to business leaders.
- Strong communication, influencing and relationship-building skills.
- Proactive, outcome-driven, comfortable with ambiguity and innovation.
- AWS and/or Databricks certifications.
- Experience with GenAI and LLM platforms in regulated (life sciences) environments.
- Familiarity with GxP, data privacy and compliance considerations in pharma.
- Product management or product-centric delivery experience.
- Delivery against milestones and effective risk and dependency management.
- Customer and stakeholder satisfaction and sentiment.
- Adoption and demonstrable business value of AI, analytics and automation initiatives.
- Reuse of patterns and accelerators across initiatives.
- Quality, reliability and compliance of AI solutions in production.
Project details
- Start: ASAP
- Duration: 12 months
- Remote: onsite
- Location: Middlesex, United Kingdom, GB
- Languages: English
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