Enrico Piovano, PhD
Co-founder & CTO at Goji AI
Building the world's most advanced AI for personalized, conversational B2B demos that turn SaaS websites into high-converting sales engines
Ex-Amazon Applied Scientist (Alexa & AGI) · Expert in Agentic AI, LLMs & ML
Writing one of the most complete blogs on Agentic AI, LLMs, and real-world applications
PhD in Electrical Engineering, Imperial College London
Gold Medalist at the National Mathematical Olympiad
About Me
Technical Expertise
I have built the entire Goji AI infrastructure from the ground up, integrating state-of-the-art Agentic AI systems and protocols (such as MCP and A2A), RAG systems, advanced search engine, LLM reasoning, fine-tuning, and reinforcement learning.
I have 6 years of experience in AI, including at Amazon, spanning Agentic AI, LLMs, and core ML including Transformer/BERT training and evaluation, offline-to-online performance correlation, data generation/cleaning, and production deployments.
Engine
Production Correlation
Evaluation
Consulting & Coaching
Consulting
Expert guidance for organizations building production-grade AI systems that deliver measurable business impact.
Agentic AI & Multi-Agent Systems
Architecture design, agent orchestration, protocol implementation (MCP, A2A)
AI Product Development
RAG systems, prompt engineering, advanced search engines, chatbox
LLM Strategy & Implementation
Fine-tuning, evaluation, and reinforcement learning
Coaching
Educational programs and knowledge transfer on Agentic AI, LLMs, RAG systems, and conversational AI to organizations upskill in the latest AI technologies.
Workshops & Seminars
Hands-on AI implementation workshops and best practices for teams
Course Development
Designing AI/ML training programs and educational curricula
Guest Lectures
Delivering insights on AI applications to academic and professional audiences
Browse One of the Largest AI/ML Engineering Blogs
Deep dives from theory to applications
One of the most extensive AI/ML engineering resources available, covering state-of-the-art techniques with the most up-to-date knowledge.
Deep dives into architectures, production patterns, latest research papers, and hands-on implementation guides.
Experience
- Multi-agent system: Connecting specialized agents and tools via MCP/A2A to seamlessly handle different tasks.
- Advanced search engine: Create an advanced LLM-based search engine to retrieve the information in SaaS website in ChatGPT search style.
- Deep context understanding: Using advanced tools and agents to extract provided context and perform background website searches to enrich the context.
- Advanced Knowledge Retrieval: An advanced RAG system that surfaces the right information and visuals (like product tours) at the right time.
- Conversational intelligence: LLM reasoning that provides the best answers and visuals, while proactively personalizing and engaging in the conversation.
- Advanced Reasoning: Applying supervised fine-tuning (SFT) and reinforcement learning (RL) to enhance reasoning and improve performance over time.
- Worked on Agentic AI and LLMs training, fine-tuning, and evaluation.
- Transformer-based natural language understanding (NLU), online performance prediction from offline metrics, synthetic data generation, dialog evaluation, offline prediction of dialog defects, and A/B testing.
- Published 3 papers in international conferences.
- Led several projects as team lead and managed two interns.
Selected achievements:
- Optimized large-scale Agentic AI systems and LLMs for improved performance and efficiency.
- Developed the key algorithm for predicting online performance from offline metrics, adopted globally across Alexa's NLU system.
- Built and deployed an NLU deep neural network (DNN) model for the German locale — Alexa's first international deployment.
- Designed and implemented new closed-loop beamforming algorithms for next-generation 802.11ah Wi-Fi modems.
- Awarded the Roberto Padovani Scholarship (one of seven best-performing interns).
Research Intern
National Research Council, Turin, Italy
Analyzed, designed, and optimized high-efficiency horn antennas.
Education
- PhD thesis on the fundamental limits of cache-aided wireless networks under various types of uncertainties.
- Investigated the high-SNR capacity of wireless networks with imperfect channel knowledge.
- Designed deep learning–based wireless communication systems for simultaneous information and power transfer.
- Published 3 papers in leading IEEE journals and 5 papers in top international conferences.
- Supervised three MSc theses on MIMO networks with imperfect CSIT.
Double MSc in Electrical Engineering and Telecommunication Engineering
Telecom ParisTech, Paris, Eurecom, Sophia Antipolis, and Politecnico di Torino, Torino
Graduated with GPA 4.0 and 110 cum laude.
BSc in Telecommunication Engineering
Politecnico di Torino, Torino
Graduated with GPA 4.0 and 110 cum laude.
Awards
Gold Medal
National Mathematical Olympiads
Silver Medal
National Mathematical Olympiads
Top Bachelor Graduate Student
Politecnico di Torino and Collegio Einaudi
Publications
Machine Learning & Conversational AI
- Predicting Interaction Quality of Conversational Assistants With Spoken Language Understanding Model ConfidencesCIKM 2023, Applied Research TrackY. Gao*, E. Piovano*, T. Soliman*, et al. (*equal contribution)
- Online Adaptive Metrics for Model Evaluation of Non-representative Offline Test DataICPR 2022 (Oral Presentation - 10% acceptance)E. Piovano, D. T. Le, B. Chen and M. Bradford
- It is better to Verify: Semi-Supervised Learning with a human in the loop for large-scale NLU modelsNAACL Workshop on Data Science with Human in the Loop, 2021V. Weber, E. Piovano and M. Bradford
- A Learning Approach to Wireless Information and Power Transfer Signal and System DesignIEEE ICASSP 2019M. Varasteh, E. Piovano and B. Clerckx
Information & Wireless Communication
- Rate-splitting multiple access for overloaded cellular internet of thingsIEEE Trans. on Communications, 2021Y. Mao, E. Piovano and B. Clerckx
- Centralized and Decentralized Cache-Aided Interference Management in Heterogeneous Parallel ChannelsIEEE Trans. on Communications, 2020E. Piovano, H. Joudeh and B. Clerckx
- Generalized Degrees of Freedom of the Symmetric Cache-Aided MISO Broadcast Channel with Partial CSITIEEE Trans. on Information Theory, 2019E. Piovano, H. Joudeh and B. Clerckx
- Optimal DoF Region of the K-User MISO BC With Partial CSITIEEE Communications Letters, 2017E. Piovano and B. Clerckx
- Robust Cache-Aided Interference Management Under Full Transmitter CooperationIEEE ISIT 2018E. Piovano, H. Joudeh and B. Clerckx
- On coded caching in the overloaded MISO broadcast channelIEEE ISIT 2017E. Piovano, H. Joudeh and B. Clerckx
- Overloaded multiuser MISO transmission with imperfect CSITAsilomar Conference 2016E. Piovano, H. Joudeh and B. Clerckx
Contact
Open for consulting, coaching, and selective advisory opportunities. Whether you're building AI products or looking to upskill your team, I'd love to hear from you.