About Pearson
At Pearson, our purpose is simple: Add life to a lifetime of learning.
As a global leader in digital learning, we are transforming how people learn through innovative, AI-powered experiences that improve outcomes and create meaningful impact. Pearson is embracing a digital-first future where AI, automation, and intelligent systems enable employees to focus on higher-value work while accelerating business transformation.
The Office of the CTO powers this transformation by delivering scalable, secure, resilient, and intelligent enterprise platforms. Within Digital & Technology (D&T), the AgentOps Team leads the next generation of enterprise automation through Agentic AI, intelligent workflows, and autonomous systems that drive measurable business value.
Why Join AgentOps?
This is an opportunity to be at the forefront of enterprise AI innovation and help shape how humans and AI agents collaborate at scale.
You will:
- Build cutting-edge agentic AI solutions deployed across Pearson's global enterprise
- Create intelligent workflows that combine automation, reasoning, and human oversight
- Solve high-impact business challenges using advanced AI technologies
- Influence enterprise-wide AI engineering and automation standards
- Help define the future of a symbiotic workforce where humans and AI agents work together seamlessly
Role Overview
The Lead Specialist, Agentic Automations is a senior practitioner and solution leader responsible for driving the end-to-end discovery, design, and delivery of enterprise-scale Agentic AI and intelligent automation solutions.
This role sits at the intersection of business strategy, process transformation, and AI engineering. You will work closely with business leaders, architects, engineers, and product teams to identify automation opportunities, design scalable agent ecosystems, and deliver solutions that generate measurable business outcomes.
As a critical member of AgentOps, you will translate complex business challenges into intelligent, AI-powered workflows while ensuring alignment with enterprise architecture, governance, risk, compliance, and ROI objectives.
You will play a key role in advancing Pearson's vision of an AI-enabled enterprise powered by agentic systems and intelligent automation.
Key Responsibilities
Business Analysis & Opportunity Discovery
- Lead end-to-end requirements gathering, process discovery, and stakeholder workshops for agentic automation initiatives.
- Analyze business processes to identify opportunities for intelligent automation, autonomous agents, and AI-driven workflow transformation.
- Facilitate cross-functional discussions with SMEs, product owners, operational teams, and business leaders.
- Document and validate business requirements, use cases, process maps, and success criteria.
- Translate business challenges into scalable AI and automation solutions with clearly defined value realization metrics.
- Establish measurable ROI, productivity, efficiency, quality, and cost optimization objectives.
Solution Design & Agentic Architecture
- Design intelligent workflows, multi-agent systems, and semi-autonomous business processes.
- Define agent behaviors, orchestration patterns, decision frameworks, escalation mechanisms, and human-in-the-loop controls.
- Create comprehensive solution artifacts including:
- Process Design Documents (PDDs)
- Solution Design Documents (SDDs)
- User Journeys
- Process Flows
- System Interaction Diagrams
- Agent Behavior Models
- Data & Integration Specifications
- Partner with architects and engineering teams to establish scalable and reusable design patterns.
- Ensure solutions align with enterprise platform, integration, security, and governance standards.
Agentic AI & Automation Delivery
- Lead the functional design and implementation of agentic automation solutions.
- Collaborate with developers, AI engineers, and automation specialists throughout the delivery lifecycle.
- Design workflows incorporating:
- Autonomous and semi-autonomous agents
- Human review and approval stages
- Escalation paths
- Exception handling
- Feedback loops
- Continuous learning mechanisms
- Drive adoption of reusable components, templates, skills, prompts, and accelerators across initiatives.
- Support enterprise rollout, change management, and operational readiness activities.
Stakeholder Management & Leadership
- Serve as the primary liaison between business stakeholders, delivery teams, and leadership.
- Communicate solution vision, business value, risks, and implementation approaches to executive and technical audiences.
- Manage competing priorities and navigate ambiguity in complex transformation programs.
- Facilitate decision-making and proactively escalate risks, dependencies, and roadblocks.
- Mentor team members and promote best practices in agentic automation delivery.
Responsible AI, Governance & Risk Management
- Ensure all solutions comply with Pearson's Responsible AI framework.
- Implement controls to mitigate:
- Hallucination risks
- Prompt injection attacks
- Data leakage
- Model misuse
- Compliance and privacy risks
- Apply governance requirements based on solution risk levels including low, medium, and high-stakes use cases.
- Support auditability, explainability, transparency, and regulatory compliance requirements.
- Partner with security, legal, privacy, and risk teams to ensure enterprise readiness.
Delivery Excellence & Business Impact
- Partner with program and project managers to ensure successful execution and delivery.
- Define and track success metrics including:
- Productivity improvements
- Cost reduction and avoidance
- Time savings
- Automation utilization
- Employee experience improvements
- Customer experience outcomes
- Ensure solutions integrate with enterprise observability, monitoring, telemetry, and governance platforms.
- Drive continuous optimization through performance measurement and feedback.
Innovation & Capability Building
- Contribute to Pearson's AgentOps roadmap and enterprise AI strategy.
- Create and maintain reusable assets including:
- Prompt libraries
- Agent templates
- Automation accelerators
- Design standards
- Playbooks and frameworks
- Evaluate emerging AI, agentic, and automation technologies.
- Champion an agentic-first mindset and culture of continuous learning across the organization.
Technology Ecosystem
Agentic AI & Large Language Models
- Azure OpenAI
- OpenAI APIs
- Claude
- Enterprise AI Platforms
- Multi-Agent Frameworks
Automation & Orchestration
- UiPath Studio
- UiPath Orchestrator
- UiPath Agent Builder
- UiPath Document Understanding
- Microsoft Power Automate
Data, Integration & Enterprise Platforms
- REST APIs
- JSON / XML
- OAuth
- Salesforce
- ServiceNow
- Oracle
- BigQuery
- OCR & Intelligent Document Processing
Engineering & Development
- Python
- JavaScript
- SQL
- Git & Version Control
- AI-Assisted Development Tools (Claude, Cursor, GitHub Copilot)
Required Qualifications
Education
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline.
- Master's degree preferred but not required.
Experience
- 8+ years of experience in technology consulting, digital transformation, automation, AI, or enterprise solution delivery.
- Demonstrated experience leading complex, cross-functional automation and AI initiatives.
- Strong experience conducting discovery workshops and translating business requirements into technology solutions.
- Proven success delivering measurable business outcomes through automation, AI, or enterprise transformation programs.
Technical & Functional Expertise
Deep understanding of:
- Agentic AI and autonomous systems
- Intelligent process automation
- Enterprise integration patterns
- Human-in-the-loop workflow design
- AI governance and Responsible AI principles
- Enterprise architecture frameworks
- Business process analysis and optimization
- Risk management, compliance, and security requirements
Leadership Competencies
- Strategic thinking and problem solving
- Exceptional stakeholder management
- Strong communication and facilitation skills
- Executive presence and influence
- Decision-making under ambiguity
- Collaboration across global and cross-functional teams
- Continuous learning and innovation mindset
Success Measures
Success in this role will be measured by:
- Enterprise adoption of agentic automation solutions
- Measurable productivity and efficiency gains
- ROI realization from automation investments
- Delivery quality and stakeholder satisfaction
- Reusability and scalability of solutions
- Compliance with Responsible AI and governance standards
- Contribution to Pearson's AI and automation transformation agenda
Pearson is committed to building a diverse, equitable, and inclusive workplace where innovation thrives and every employee can contribute to shaping the future of learning through AI and technology.
Join us in building the future of work, where humans and intelligent agents collaborate to create extraordinary outcomes.