Position Summary We are seeking an accomplished and visionary Director – Data Science, Data Engineering, AI Solutions & Pre-Sales to lead our AI and Data practice, drive strategic growth, and deliver transformative solutions for global clients. This role combines executive leadership, solution architecture, business development, pre-sales consulting, and delivery oversight across Data Engineering, Data Science, Artificial Intelligence, Generative AI, Analytics, and Cloud platforms. The ideal candidate will have a strong blend of technical depth, consulting expertise, client-facing leadership, and business acumen, with a proven ability to build high-performing teams, win strategic opportunities, and deliver measurable business outcomes through data-driven innovation. Location: Hyderabad,India Key Responsibilities Strategic Leadership & Practice Growth • Define and execute the organization's Data, Analytics, AI, and Generative AI strategy aligned with business objectives. • Build and scale a high-performing Data & AI practice, including Data Engineering, Data Science, AI/ML, GenAI, and Solution Architecture capabilities. • Develop go-to-market strategies, solution offerings, accelerators, and industry-specific frameworks. • Drive revenue growth, profitability, and market expansion for the Data & AI portfolio. • Establish thought leadership through industry events, executive forums, whitepapers, and client engagements. AI, Data Science & Analytics Leadership • Lead the design, development, and deployment of advanced AI/ML, Generative AI, predictive analytics, NLP, recommendation engines, and intelligent automation solutions. • Define AI adoption roadmaps and enterprise AI strategies for clients. • Drive innovation using Large Language Models (LLMs), RAG architectures, Agentic AI, and AI governance frameworks. • Ensure implementation of Responsible AI, model governance, and enterprise AI best practices. • Oversee AI solution delivery from ideation through production deployment and value realization. Data Engineering & Cloud Transformation • Lead enterprise-scale data modernization and cloud transformation initiatives. • Architect and implement scalable data platforms, data lakes, lakehouses, data warehouses, and real-time streaming solutions. • Define enterprise data governance, security, metadata management, and data quality strategies. • Drive adoption of modern cloud ecosystems and data platforms across AWS, Azure, and GCP. • Establish DataOps and MLOps practices to improve operational efficiency and scalability. Solution Architecture & Consulting • Serve as executive sponsor and chief solution architect for strategic customer engagements. • Design end-to-end business and technology solutions that address complex customer challenges. • Lead architecture reviews, solution blueprints, transformation roadmaps, and implementation strategies. • Provide guidance on enterprise architecture, cloud modernization, AI adoption, and digital transformation programs. • Ensure solution scalability, performance, security, and compliance. Pre-Sales & Business Development • Partner with sales leadership to identify, qualify, and close strategic opportunities. • Lead client discovery workshops, executive presentations, capability demonstrations, and solution discussions. • Own RFP, RFI, RFQ responses, solution estimation, pricing strategies, and proposal development. • Develop compelling value propositions, business cases, and ROI frameworks for clients. • Build and maintain trusted relationships with C-level executives, business leaders, and technology stakeholders. • Support strategic account growth and large transformation pursuits. Leadership & Talent Development • Build, mentor, and retain high-performing teams of Data Scientists, Data Engineers, AI Specialists, Architects, and Consultants. • Establish a culture of innovation, collaboration, accountability, and continuous learning. • Drive workforce planning, capability development, succession planning, and leadership grooming. • Foster strong collaboration across delivery, sales, product, engineering, and business teams. Required Qualifications Education • Bachelor's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related discipline. • Master's degree (MBA, M.Tech, MS, MCA, or equivalent) in Computer Science, Artificial Intelligence, Data Science, Analytics, Engineering, Business Administration, or a related field is strongly preferred. • Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Statistics, or a related discipline is highly desirable. Professional Experience • 18+ years of overall experience in Data Engineering, Data Science, Analytics, Artificial Intelligence, Cloud Technologies, or Digital Transformation. • 8+ years of experience leading large-scale Data & AI practices, consulting organizations, or technology teams. • Proven success in delivering enterprise-scale AI, analytics, and data transformation programs. • Demonstrated experience managing P&L, practice growth, business development, and strategic client relationships. • Strong experience supporting pre-sales, solution consulting, proposal development, and large deal pursuits. Technical Expertise • Machine Learning, Deep Learning, Predictive Analytics, and Statistical Modeling. • Generative AI, Large Language Models (LLMs), RAG, Agentic AI, NLP, and AI Governance. • Data Engineering, Data Warehousing, Data Lakes, Lakehouse Architectures, and Real-Time Data Platforms. • Cloud Platforms: AWS, Microsoft Azure, and Google Cloud Platform (GCP). • Big Data Technologies: Spark, Databricks, Hadoop Ecosystem, Kafka, and Distributed Computing. • MLOps, DataOps, CI/CD, Model Monitoring, and AI Lifecycle Management. • Enterprise Architecture, Solution Design, and Cloud-Native Application Architectures. Leadership Competencies • Strong executive presence with exceptional communication and presentation skills. • Ability to influence senior stakeholders and C-level executives. • Strategic thinking with strong business and commercial acumen. • Proven people leadership, mentoring, and organizational development experience. • Ability to lead global, cross-functional, and geographically distributed teams. Preferred Certifications • AWS Certified Solutions Architect – Professional • Microsoft Certified: Azure Solutions Architect Expert • Google Professional Cloud Architect • Databricks Certified Data Engineer or Data Architect • AI/ML Certifications from AWS, Azure, GCP, or equivalent • TOGAF, SAFe, PMP, or Enterprise Architecture Certifications Key Success Metrics • Revenue growth and profitability of the Data & AI practice. • Successful acquisition and closure of strategic opportunities. • Client satisfaction, retention, and business expansion. • Delivery of scalable AI and Data solutions with measurable business impact. • Team growth, leadership development, and employee retention. • Innovation, thought leadership, and market differentiation.