HCLTech
Website:
hcltech.com
Job details:
About the Company
HCLTech is a global leader in technology and digital transformation, recognized for delivering innovative solutions across more than 50 countries. With a diverse workforce and a strong focus on customer-centricity, HCLTech is committed to driving business outcomes through technology innovation, operational excellence, and a culture of continuous improvement. The company is celebrated for its collaborative approach, award-winning solutions, and dedication to fostering a sustainable and inclusive global community.
About the Role
The AI Leader will drive the strategic design, development, and implementation of AI-powered solutions across Digital Process Outsourcing operations. This role combines deep technical expertise with strong business understanding to automate processes, improve operational efficiency, enhance customer experience, and enable new digital service capabilities.
Responsibilities
AI Strategy & Leadership
- Define and execute the AI roadmap for DPO services, aligned with organizational goals.
- Identify high-impact AI use cases across operations, service delivery, and customer experience.
- Champion innovation by evaluating new AI technologies and automation platforms.
Solution Design & Delivery
- Lead end-to-end development of AI solutions including conversational AI, intelligent automation, predictive analytics, and generative AI capabilities.
- Architect scalable AI systems that integrate with existing DPO tools, CRM, BPM, and workflow systems.
- Guide data scientists, engineers, and automation teams in building production-ready models and solutions.
Operational Excellence
- Drive automation-led transformation of business processes to reduce cost, improve SLA adherence, and enhance quality.
- Introduce AI governance, measurement frameworks, and performance KPIs for AI solutions.
- Ensure robust monitoring, retraining, and lifecycle management of models in production.
Stakeholder & Client Management
- Work closely with delivery leaders, business heads, and clients to understand requirements and propose AI-driven solutions.
- Present AI concepts, ROI analysis, and implementation plans to internal and external stakeholders.
- Partner with sales teams to build AI-enabled offerings and support pre-sales activities.
Risk, Compliance & Responsible AI
- Ensure solutions follow responsible AI principles, including fairness, transparency, and security.
- Maintain compliance with data privacy regulations and client-specific governance guidelines.
- Oversee model risk assessments and ethical AI reviews.
Education Qualifications
- Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related fields.
- Advanced certification in AI/ML, automation, or data analytics preferred.
Experience
- 10+ years of experience in AI, ML, automation, or advanced analytics roles.
- At least 5 years in leadership roles driving transformation in BPO/DPO, ITES, or shared services.
- Proven track record of deploying AI or automation at scale in operations-heavy environments.
Required Skills
- Expertise in machine learning, NLP, computer vision, and generative AI models.
- Strong understanding of automation platforms (UiPath, Automation Anywhere, Blue Prism).
- Proficiency with AI/ML tools and frameworks (Python, TensorFlow, PyTorch, Azure ML, etc.).
- Knowledge of cloud platforms (Azure, AWS, GCP) and data engineering.
Preferred Skills
- Strong program management and stakeholder engagement abilities.
- Excellent communication skills with the ability to simplify technical concepts.
- Demonstrated ability to deliver measurable business impact through AI.
Key Performance Indicators (KPIs):
Automation & Efficiency Metrics
- % Reduction in Process Cycle Time (PCT) achieved through AI/automation.
- Average Handle Time (AHT) reduction in customer or back‑office processes.
- % Increase in First Pass Yield (FPY) or accuracy due to AI-based enhancements.
- Volume of tasks automated (FTE savings, hours automated, bots deployed).
AI Solution Adoption & Scaling
- Adoption rate of AI solutions across DPO business units (number of processes/LOBs scaled).
- Operational uptime & performance of AI models (accuracy, precision, recall, SLA adherence).
- % of AI models successfully moved from POC to production.
Financial Impact
- Cost savings delivered through AI-driven process re‑engineering and automation.
- Revenue influenced or generated through AI-powered offerings or new digital services.
- ROI of AI initiatives within specified timelines.
Quality & Customer Experience
- Improvement in customer satisfaction (CSAT/NPS) after AI solution deployment.
- Reduction in error rates and quality defects due to AI-based validation and decisioning.
- % improvement in SLA compliance across DPO services.
Innovation & Transformation
- Number of new AI use cases identified, validated, and delivered annually.
- Introduction of advanced AI technologies (genAI, predictive models, intelligent workflows).
- Time-to-value for AI pilots from ideation to deployment.
Data & Responsible AI Governance
- Compliance with data privacy and responsible AI frameworks (incidents, audit results).
- Model accuracy drift & retraining frequency managed proactively.
- Risk mitigation effectiveness for AI models in production.
Stakeholder & Client Engagement
- Client satisfaction with AI-led transformation programs.
- Number of client engagements supported with AI consulting or pre-sales.
- Quality and clarity of AI solution proposals, including business case and ROI modeling.
Team Leadership & Capability Building
- Upskilling % of the workforce on AI/ML, automation, and digital tools.
- Team performance metrics (delivery quality, innovation, collaboration).
- Strength of AI talent pipeline (hiring, training, certifications).
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