Head – Digital Service Lab, GSC

Key Responsibilities

Transformational Impact

This role directly enables GSC’s accelerated digitalization program through AI‑first operations, Agentic AI workflows, and playbooks for enterprise scaling—working closely with business stakeholders, IT, vendors, and the Process Automation team for transition to production.

Strategy, Vision & Operating Model

• Define and lead the Digital Service Lab vision and operating model aligned with GSC’s accelerated digitalization roadmap.
• Develop a multi-year innovation roadmap across:
  • GenAI & Agentic AI
  • Intelligent automation
  • LLM-driven process enhancements
  • Intelligent document processing
  • Conversational AI
  • Analytics, insights & decision intelligence
• Establish standards for discovery, rapid prototyping, controlled experimentation, and readiness for scale.
• Ensure alignment with organizational transformation priorities and enterprise architecture.

Innovation, Experimentation & Solutioning

• Operate the Lab as a rapid innovation sandbox for evaluating business problems, exploring solution patterns, and validating concepts.
• Lead structured discovery to identify customer pain points, feasibility, and value opportunities.
• Drive PoCs, MVPs, and early pilots with clear hypotheses, measurable outcomes, and rapid iteration cycles.
• Evaluate build vs. buy options leveraging internal capabilities, external platforms, startups, and partners.
• Ensure solutions meet user needs and align with long-term scalability.

Build + Buy/Partner Approach

• Identify and evaluate external platforms, SaaS providers, AI partners, and niche startups that accelerate innovation outcomes.
• Conduct vendor assessments, proof-of-value analyses, and due diligence covering security, compliance, and performance.
• Lead vendor collaboration and negotiation activities in partnership with procurement and security teams.
• Build co‑innovation opportunities where external solutions complement internal strengths.

Engineering, Integration & Technical Governance

• Guide design, architecture, integration, and testing approaches in partnership with IT and enterprise architecture.
• Define standards for:
  • AI & GenAI guardrails
  • AI governance and risk assessment
  • Automation architecture
  • Integration patterns
  • LLMOps, AIOps & model lifecycle disciplines
• Ensure solutions are secure, scalable, compliant, and ready for transition into formal delivery teams.

Value Realization & Scaling Transition

• Plan and oversee the transition from Lab-to-Scale to the Process Automation team once solutions are validated.
• Establish clear performance KPIs, ROI measures, adoption metrics, and value realization frameworks.
• Create solution playbooks for IDP, Conversational AI, and Agentic AI.
• Track outcomes, report benefits, and maintain visibility with leadership.

Leadership, Capability & Culture Building

• Lead a multidisciplinary team of technical and innovation specialists across AI/ML, data science, product experimentation, and analytics.
• Build emerging skillsets including prompt engineering, Agentic AI design, LLMOps, AIOps, and AI governance.
• Foster a culture of curiosity, rapid iteration, experimentation, and evidence-based decision-making.
• Strengthen capability uplift through coaching, training, certifications, and communities of practice.

Stakeholder Management

• Engage senior business leaders within GSC to shape problem statements, explore opportunities, and co-create solutions.
• Coordinate with external partners, technology providers, consulting teams, and ecosystem players.
• Communicate outcomes, opportunities, risks, and value to both technical and non-technical audiences.
• Influence cross-functional leadership to adopt innovative approaches.

Qualification & Requirements

Education & Experience

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.
• 12–18+ years of experience in AI, automation, digital innovation, or technology-driven transformation roles.
• Minimum 5–8 years leading innovation labs, digital transformation teams, AI/automation portfolios, or similar functions.
• Experience collaborating with internal teams, IT, vendors, and cross-functional stakeholders.

Technical Skills & Innovation

• Strong expertise in AI/ML, GenAI, NLP, LLMs, RAG, IDP, intelligent automation, and emerging Agentic AI patterns.
• Deep understanding of RPA/IPA, process mining, workflow orchestration, intelligent document processing, and conversational AI.
• Strong understanding of cloud-native AI/ML services (Azure, AWS, GCP), integration patterns, and secure design.
• Ability to architect experiments, validate hypotheses, run PoCs, and define pathways to scale.
• Proven experience in Responsible AI practices, including model governance, security & compliance

Preferred / Strongly Desirable Capabilities

• Prompt engineering
• Agentic AI design & evaluation
• Data engineering
• LLMOps
• AIOps
• AI governance & risk

Leadership & Behavioural

• Strategic thinker with the ability to convert complex business needs into innovative digital solutions.
• Blend of strategic leadership and hands‑on technical direction.
• Strong stakeholder influence, communication, and relationship-building skills.
• Comfortable operating in ambiguity, driving clarity, and leading high-velocity experimentation cycles.

Benefits

No information available.