Head of Engineering (Data, ML and AI Tools)
- Lead and scale our cross-functional ML and data engineering teams, including machine learning engineers, LLM/AI engineers, data analysts, and Software engineers.
- Drive the development of intelligent tools for customer agents (e.g., LLM-based AnswerBots) and end-users (e.g., VoiceBots) that improve service efficiency and experience.
- Guide the team delivering predictive ML models for utility clients in areas like water leak detection and churn prediction, ensuring robustness, explainability, and client value.
- Oversee the development of data analytics products - including dashboards and data pipelines - that deliver actionable intelligence to utility clients.
- Set the long-term technical vision for our AI & analytics products while being hands-on in system design, architecture reviews, and high-impact technical decisions.
- Partner closely with cross-functional stakeholders, including product managers, customer teams, and delivery leads, to align technical solutions with business goals.
- Champion experimentation, prototyping, and fast iteration to explore new use cases with GenAI and classic ML across business domains.
- Build systems that combine structured data, unstructured customer interactions, and real-time operational signals, powering the next generation of intelligent decision support.
- Stay on the forefront of emerging technologies in LLMs, RAG (Retrieval-Augmented Generation), reinforcement learning, and agentic workflows - and translate them into practical, scalable products.
- Proven leadership experience in managing multi-disciplinary engineering teams (20+ engineers), including ML, LLM, data engineering, and platform engineering.
- Understanding of ML lifecycle - from data ingestion and feature engineering to model training, evaluation, and deployment in production.
- Hands-on experience deploying LLM-based systems (e.g., RAG pipelines, tool calling, fine-tuning, RLHF) and integrating them into real-world applications.
- Experience developing customer-facing AI tools, voice-based interfaces, or agent augmentation systems is highly desirable.
- Strong architectural skills and the ability to make pragmatic decisions between prototypes and production-grade systems.
- Experience building and operating robust data pipelines, ETL frameworks, and analytics dashboards that serve clients in regulated industries like water or telco.
- Familiarity with modern AI/ML stacks: Python, Kubernetes, PyTorch, LangChain, vector databases, etc.
- Demonstrated ability to align AI and analytics initiatives with business outcomes and customer value.
- Inspirational leadership style with a strong product sense and ability to lead through ambiguity. Experience managing teams of teams (20+ engineers is desired)
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