HCLTech
Website:
hcltech.com
Job details:
About the Company
We are seeking a seasoned AI Practice Lead with 15+ years of comprehensive experience to spearhead client engagements and drive custom AI solution development across diverse industry verticals. This executive-level role combines deep technical expertise in Generative AI, Machine Learning, and Deep Learning with exceptional client management skills and strategic business acumen to identify and capitalize on AI opportunities in the rapidly evolving artificial intelligence landscape.
About the Role
Position Overview
Experience Required:
- 15+ years in AI/ML with 8+ years in leadership roles
Location:
- Noida/Bangalore/Mumbai (preferred), open to other major tech hubs
Travel:
- Extensive travel required for client meetings, solution presentations, and global AI conferences
Industry Focus:
- Cross-industry AI solutions with expertise in BFSI, Healthcare, Manufacturing, Retail, and Emerging Technologies
Responsibilities
- Client Engagement & Business Development
- Lead high-stakes client interactions, serving as the primary AI evangelist and technical authority
- Conduct executive-level presentations on AI strategy, ROI analysis, and digital transformation roadmaps
- Identify and qualify AI opportunities across diverse industry domains through consultative selling approaches
- Build and maintain C-suite relationships with enterprise clients, technology partners, and industry leaders
- Drive revenue generation through strategic AI solution positioning and competitive differentiation
- AI Solution Architecture & Design
- Architect end-to-end AI solutions encompassing Generative AI, Traditional ML, Deep Learning, and Large Language Models
- Design custom AI frameworks with built-in explainability, interpretability, and transparency mechanisms
- Develop comprehensive AI governance frameworks including ethical guidelines, bias detection, and fairness metrics
- Create robust security architectures for AI systems including adversarial attack protection and privacy preservation
- Lead proof-of-concept development and technical validation for complex AI implementations
- Practice Development & Innovation
- Define and execute AI practice strategy, including service offerings, capability development, and market positioning
- Stay ahead of emerging AI trends including multimodal AI, federated learning, quantum ML, and neuromorphic computing
- Establish partnerships with leading AI research institutions, technology vendors, and startup ecosystems
- Drive thought leadership through whitepapers, industry publications, speaking engagements, and patent filings
- Build and mentor high-performing AI teams across technical and business functions
- Technical Leadership & Delivery Advanced AI Technologies
- Lead implementation of Generative AI solutions including GPT variants, diffusion models, and multimodal generative systems
- Architect Large Language Model (LLM) solutions with focus on domain adaptation, fine-tuning, and prompt engineering
- Design and implement sophisticated ML algorithms including ensemble methods, reinforcement learning, and transfer learning
- Develop Deep Learning architectures for computer vision, natural language processing, and time series analysis
- Create federated learning systems for privacy-preserving AI across distributed environments
- Explainable AI & Governance
- Implement comprehensive explainable AI (XAI) frameworks using LIME, SHAP, attention mechanisms, and custom interpretability tools
- Design AI governance structures including model monitoring, drift detection, and automated retraining pipelines
- Establish ethical AI guidelines with focus on fairness, accountability, transparency, and human-centered design
- Create robust testing frameworks for AI bias detection, adversarial robustness, and safety validation
- Implement AI audit trails and compliance reporting for regulatory requirements
- Technical Implementation & Platforms
- Hands-on development using Python ecosystem including TensorFlow, PyTorch, Scikit-learn, Hugging Face, and LangChain
- Design cloud-native AI architectures on AWS, Azure, and GCP with focus on scalability and cost optimization
- Implement MLOps pipelines including automated testing, deployment, monitoring, and lifecycle management
- Develop real-time AI inference systems with low-latency requirements and high-availability constraints
- Create hybrid AI solutions combining on-premises and cloud deployments for security-sensitive applications
Qualifications
- Executive & Leadership Skills
- Strategic Vision: Proven ability to translate AI possibilities into business value and competitive advantage
- Client Management: Exceptional skills in managing enterprise relationships and driving complex sales cycles
- Team Leadership: Experience building and scaling AI teams from startup to enterprise levels
- Communication: Outstanding presentation skills with ability to communicate technical concepts to non-technical executives
- Business Acumen: Deep understanding of AI economics, pricing models, and market dynamics
- Technical Expertise
- Generative AI Mastery: Extensive experience with GPT, BERT, T5, diffusion models, GANs, and multimodal architectures
- ML/DL Proficiency: Advanced knowledge of supervised, unsupervised, and reinforcement learning algorithms
- Python Expertise: Expert-level proficiency in Python for data science, ML frameworks, and production systems
- Data Engineering: Strong background in data pipelines, feature engineering, and data architecture
- Cloud Platforms: Hands-on experience with cloud AI services and distributed computing frameworks
- Industry & Domain Knowledge
- Cross-Industry Experience: Proven track record of delivering AI solutions across multiple industry verticals
- Regulatory Awareness: Understanding of AI regulations, data privacy
Click on Apply to know more.