At a Glance
- Tasks: Transform operational data into AI-driven insights for service delivery and contract management.
- Company: Join a forward-thinking company focused on AI and operational excellence.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Fast-paced environment with a focus on innovation and teamwork.
- Why this job: Make a real impact by optimising processes and enhancing productivity with AI.
- Qualifications: Experience in operations, strong analytical skills, and a passion for continuous improvement.
The predicted salary is between 60000 - 80000 Β£ per year.
The Service Delivery & Contract Management AI Product Owner is a combined role that owns two connected domains of AI-enabled operational improvement: the service delivery framework and the contract management decision logic. Across both domains, this role transforms operational data into predictable, explainable, and auditable guidance β driving productivity improvements in work order management and ensuring service contract decisions are consistent, evidence-based, and optimized across the asset fleet.
This role designs and governs AI-powered assistants that support engineers, planners, operational teams, and commercial stakeholders by:
- Improving work order quality and reducing approval delays
- Enabling proactive maintenance and root cause identification
- Ensuring the right vendor is engaged quickly
- Delivering consistent, defensible contract recommendations
- Supporting renewal decisions and retrospective contract performance reviews
This role does not build AI models or write code. It defines what questions the AI can answer, what data it uses, what rules it follows, and how recommendations are explained. The role holder must bring a marginal gains mindset β continuously improving processes for ongoing productivity gains.
Key Responsibilities
- Work Order Productivity & Process Improvement
Drive measurable productivity improvements in the work order management process. Map the work order lifecycle (creation β triage β execution β closure). Identify non-value-adding steps, rework loops, approval delays, and manual handoffs that AI-assisted guidance could help eliminate or reduce. Apply lean principles to reduce:- Number of work order steps
- Work order handling time
- Administrative effort for engineers and planners
- Proactive Service Management & Alerts
Lead the shift from reactive repairs to proactive service intervention. Define how service alerts are generated based on failure history, downtime trends, utilization intensity, and asset age. Establish clear thresholds for early intervention. Ensure proactive insights are explainable, actionable, and trusted by frontline teams. - Root Cause Analysis & Repeat Repair Identification
Strengthen identification of the true underlying causes of equipment failures. Define how root cause evidence is captured and interpreted in ServiceMax. Use structured data and work order notes to distinguish repeat faults, identify systemic failure patterns, and reduce symptom-based fixes. Ensure root cause insights inform service strategy and preventive actions. - AI Assistant & Virtual Work Order Specialist
Define and govern an AI assistant that acts as a virtual work order specialist. Specify functional requirements for an agent that supports correct work order creation, prompts for missing information, and surfaces relevant historical service insights. Define where the agent may initiate the front end of service requests or communications via ServiceMax integrations. Ensure outputs clearly explain: what is happening, why it matters, what action is recommended, and what alternatives exist. - Vendor Performance & Capability Insights
Provide visibility into vendor performance beyond individual assets. Define how vendor trends are analyzed across asset classes, sites or regions, and response and resolution times. Support identification of appropriate vendors when assets are not on contract. Enable comparisons based on capability, speed of response, and repeat visit rates. - Define What Good Looks Like for Contract Recommendations
Specify mandatory elements for every AI contract recommendation, including:- Contract status and entitlement
- Warranty position
- Asset criticality and utilization
- Failure and downtime history
- Strategic supplier linkage (e.g. wider supplier grouping)
- Contract Data Ownership & Quality
Own the contract data model linking assets, contracts, entitlements, and work orders. Identify and take accountability to rectify data quality gaps in OneSource / ServiceMax. Maintain the system linkage between contract records and operational performance data. - Contract Decision Rules
Translate operational practice into decision logic, including:- Non-negotiable rules (warranty, regulatory)
- Best-practice guidance (risk-based coverage)
- Prioritization logic (criticality vs redundancy vs cost vs uptime)
- Retrospective review logic β have the right decisions historically been made on this asset?
- Ad hoc spend vs contract spend
- Service & Contract AI Tool Design & Wireframing
Define functional requirements and wireframes across both domains for:- Work order guidance and automation
- Failure risk indicators and PM effectiveness assessments
- Contract suitability assessments
- Renewal recommendations and stakeholder engagement workflows
- Validation, Adoption & Continuous Improvement
Lead user validation with engineers, operations leads, FM, sourcing, and end users. Review overridden or rejected recommendations in both service and contract domains. Update rules as contracts, suppliers, service strategies, or policies change. Monitor recommendation accuracy, relevance, and data drift over time. - Service Data Mapping & Integrity
Own the service data model linking: Assets β Work Orders β Failure Modes β Outcomes. Identify data gaps, inconsistencies, and misclassification. Define data standards required to support service insights, productivity analysis, and AI-supported recommendations.
Critical Skills
- Must have strong understanding of operations, service contracts, warranties, and asset risk.
- Must have high data literacy β able to work with data and interpret analytical outputs without coding experience.
- Must have proven analytical experience.
- Must have demonstrated ability to convert tacit operational knowledge into explicit, auditable rules.
- Must have strong stakeholder facilitation and governance discipline.
- Must have a marginal gains mindset β committed to continuous process improvement and ongoing productivity gains.
Basic Qualifications:
Bachelors Degree and 7+ years of relevant work experience OR Associates Degree and 9+ years of relevant work experience OR Highschool Diploma and 12+ years of relevant work experience.
Working Environment:
Job pace may be fast and job completion demands may be high. Must be able to remain in a stationary position more than 25% of the time. Occasionally move or lift up to 25 pounds (potential for occasional lifting of up to 50 pounds). Occasionally operates a computer and other office machinery, such as a calculator, copy machine, and computer printer.
Service Delivery & Contract Management AI Product Owner employer: PerkinElmer
Contact Detail:
PerkinElmer Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Service Delivery & Contract Management AI Product Owner
β¨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend events, join online forums, or even hit up LinkedIn. The more people you know, the better your chances of landing that dream job.
β¨Tip Number 2
Prepare for interviews by researching the company and role inside out. Know their values, recent projects, and how your skills can help them achieve their goals. This shows you're genuinely interested and ready to contribute.
β¨Tip Number 3
Practice makes perfect! Do mock interviews with friends or use online tools to get comfortable with common questions. The more you practice, the more confident you'll feel when itβs time to shine.
β¨Tip Number 4
Donβt forget to follow up after interviews! A quick thank-you email can go a long way in keeping you top of mind. Plus, it shows your enthusiasm for the role and appreciation for their time.
We think you need these skills to ace Service Delivery & Contract Management AI Product Owner
Some tips for your application π«‘
Tailor Your Application: Make sure to customise your CV and cover letter for the Service Delivery & Contract Management AI Product Owner role. Highlight your experience with operational improvement and data analysis, as these are key aspects of the job.
Showcase Your Analytical Skills: Since this role requires a strong understanding of data and analytics, be sure to include examples of how you've used data to drive decisions or improve processes in your previous roles. We love seeing those marginal gains!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use bullet points where possible to make your achievements stand out. We appreciate clarity and directness in communication!
Apply Through Our Website: Donβt forget to submit your application through our website! Itβs the best way for us to receive your details and ensures youβre considered for the role. We canβt wait to see what you bring to the table!
How to prepare for a job interview at PerkinElmer
β¨Know Your AI Basics
Even though this role doesn't require coding, understanding the fundamentals of AI and how it can be applied in service delivery and contract management is crucial. Brush up on key concepts and think about how AI can improve operational processes.
β¨Showcase Your Analytical Skills
Prepare to discuss your experience with data analysis and how you've used data to drive decisions in previous roles. Be ready to provide examples of how you've identified inefficiencies and implemented improvements, as this aligns perfectly with the marginal gains mindset.
β¨Understand the Work Order Lifecycle
Familiarise yourself with the work order lifecycle from creation to closure. Think about how you would map this process and identify non-value-adding steps. Being able to articulate this during the interview will demonstrate your proactive approach to service management.
β¨Prepare for Stakeholder Scenarios
Since this role involves working with various stakeholders, prepare for questions around stakeholder facilitation. Think of examples where you've successfully engaged different teams or individuals to achieve a common goal, showcasing your governance discipline.