Lead Specialist, Technology Solutions - Agentic Automations

Pearson; Chennai District; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Pearson is seeking a Lead Specialist, Agentic Automations to drive end-to-end discovery, design, and delivery of intelligent automation solutions. You will collaborate with business leaders, architects, and engineers to identify opportunities, design scalable agentic ecosystems, and deliver measurable outcomes aligned with enterprise architecture and ROI objectives.

You will advance Pearson's AI-enabled enterprise vision, champion governance, risk, and continuous learning, while mentoring teams

Qualifications

• Bachelor's degree in CS, Engineering, Information Systems, or related discipline.
• Master's degree preferred but not required.
• 8+ years in technology consulting, digital transformation, automation, AI, or enterprise delivery.
• Experience leading complex cross-functional automation and AI initiatives.
• Proven ability to translate business requirements into technology solutions.
• Strong governance, risk, and Responsible AI awareness.

Responsibilities

• Lead end-to-end discovery, design, and delivery of enterprise-scale agentic automation.
• Design intelligent workflows, multi-agent systems, and human-in-the-loop controls.
• Collaborate with architects, engineers, and product teams across delivery lifecycles.
• Establish ROI, productivity, and cost-optimization objectives.
• Mentor teams and promote best practices in agentic automation delivery.
• Ensure compliance with Responsible AI and governance standards.

Skills

Agentic AI

Automation

Stakeholder management

Requirements gathering

Cross-functional collaboration

Education

Bachelor's degree in Computer Science/Engineering/Information Systems

Master's degree preferred

Tools

Azure OpenAI

OpenAI APIs

Claude

UiPath/Automation tools

REST APIs

JSON/XML

OAuth

Salesforce

ServiceNow

Oracle

BigQuery

Python

JavaScript

SQL

Git

GitHub Copilot

Job description

Job Summary

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 Pearsons vision of an AI-enabled enterprise powered by agentic systems and intelligent automation.

Key Responsibilities

Business Analysis

• 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

• 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 engage 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

• 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

• 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.

Capability Building

• Contribute to Pearsons AgentOps roadmap and enterprise AI strategy.

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, 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

• 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

• 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