• Define and own the enterprise AI, ML strategy, building a multi-year roadmap aligned to digital and business transformation priorities
• Lead and scale a high-performing team of AI Engineers, MLOps Engineers, Data Engineers, Application Engineers and Data Scientists
• Architect and oversee development of enterprise-grade AI solutions including LLM-based systems, Retrieval-Augmented Generation (RAG), predictive ML models, decision intelligence platforms, and data-heavy applications
• Drive the full AI product lifecycle - opportunity discovery, business case definition, architecture design, development, deployment, monitoring, optimization and value realization
• Establish enterprise AI reference architectures, reusable frameworks, modular ML templates and standardized deployment patterns
• Ensure strong MLOps maturity including CI/CD for ML, model registry, automated retraining pipelines, monitoring for data/model drift, observability and governance
• Lead cloud-native AI platform strategy leveraging Azure / Databricks / AWS / GCP ecosystems with focus on scalability, resiliency and cost efficiency
• Define GenAI standards including prompt engineering frameworks, evaluation pipelines, guardrails, responsible AI controls and security compliance
• Partner with business leaders to translate complex operational challenges into scalable AI and data products with measurable ROI
• Define and track product KPIs including adoption, performance, latency, uptime, cost per inference, business value creation and productivity uplift
• Ensure enterprise-grade security, compliance, and responsible AI practices across all deployed solutions
• Drive continuous innovation by evaluating emerging AI technologies and integrating them into the enterprise ecosystem where strategically relevant
• Act as the single point of accountability for AI & Data product performance, delivery excellence and long-term platform scalability
YOUR TALENT• University degree (B.Tech / M.Tech / M.S.) in Computer Science, Engineering or related discipline; MBA or equivalent business exposure is a plus
• 12+ years of experience across AI/ML, Data Platforms, or Enterprise Product Engineering, with 5+ years leading cross-functional technical teams
• Proven track record of building and scaling enterprise AI/ML products in production environments
• Deep understanding of:
Machine Learning lifecycle and model governance
LLMs, transformer architectures, RAG pipelines and prompt engineering strategies
MLOps frameworks including model monitoring, drift detection, retraining and CI/CD for ML
Modern data architectures (Databricks, Spark, ETL/ELT, Delta patterns, data orchestration)
API-driven architectures and distributed systems design
• Strong exposure to cloud ecosystems (Azure, Databricks, AWS or GCP) and cost optimization strategies for large-scale AI workloads
• Experience designing scalable, secure and highly available enterprise data platforms
• Strong strategic thinking with ability to align AI investments to business value, operational efficiency and competitive advantage
• Demonstrated experience influencing senior stakeholders and translating technical trade-offs into business decisions
• Strong leadership and talent development capability, with experience building engineering culture and technical maturity
• Excellent communication skills with ability to operate across business and technical audiences
• Hands-on mindset with ability to dive deep into architecture discussions when required
• Ability to operate in a fast-paced, high-growth and transformation-driven environment
• Fluent in Business English
SPEED & SPIRIT is what we look for in our candidates, defined by some simple values that inspire us to BE DRIVEN in our performance, BE VIBRANT in our sporting legacy, BE TOGETHER in our team spirit, and BE YOU to let our individual talent and experience shine. Applying for a job at PUMA is easy. Simply click APPLY ONLINE and follow the steps to upload your application.
