We are one of the leading technology groups in Italy. We operate as a Business & Technology Accelerator for companies, financial institutions, and public sector organizations, supporting the evolution of their IT and digital strategies. Through an ecosystem of companies that share values, business strategies, and a common vision, we enable our clients to unlock the full potential of technology, amplifying its positive impact on both the economy and society.

What to expect

As our AI Solutions Consultant for Data Cleansing Services, you are the face and the engine of our MRO data quality product. You are not operating in a silo. Before a contract is even signed, you will partner directly with the Pre-Sales team, stepping into client pitches to prove technical feasibility and explain exactly how our AI will resolve their specific industrial data nightmares. Once the raw MRO data lands, you will operate our proprietary transformation pipeline—balancing deterministic rules with cutting-edge LLM agents—to ingest, clean, and standardize it. You own the iterative post-sale feedback loop: running the data, performing rigorous QA, presenting preliminary results, and instantly tweaking prompts or rules based on client feedback until the output is fully validated and standardized. Throughout it all, you will work alongside our Product Management and core Engineering teams, acting as the critical frontline scout who aligns our pipeline's specs with real-world chaos, identifies edge cases, and reports operational bugs.

What you will do

• Operate the internal data transformation pipeline. Revise, test, and optimize LLM prompts and deterministic rules based on preliminary outputs and client feedback to maximize accuracy.

• Manage the end-to-end client data journey. Ingest raw data, securely deliver processed results, and actively manage the iterative feedback loops with the customer.

• Act as the frontline scout for our technical teams. Report operational bugs, troubleshoot runtime issues with developers, and provide the frontline insights Product needs to shape the pipeline's future roadmap and functional specifications.

• Partner with the Sales team during client pitches. Act as the Subject Matter Expert who can confidently explain how our deterministic rules and LLM agents work together to solve their specific data nightmares.

• Conduct rigorous ad-hoc data profiling using tools like SQL, Python, or Excel to identify structural anomalies before the client ever sees them. Evaluate preliminary pipeline outputs for strict quality assurance.

• Establish and track core data quality metrics to prove completeness and consistency to the client. Meticulously document pipeline configurations, rule modifications, and prompt versioning to ensure operational reproducibility.

What we expect from you

• MRO Data Mastery: Deep proficiency in the MRO (Maintenance, Repair, and Operations) sector. You must intimately understand the shape, scale, and chaos of industrial MRO data—knowing its typical content, common structural problems, expected volumes, and exactly what "good," production-ready data looks like in this specific industry.

• High-level communication skills are non-negotiable. You must be able to confidently present technical data concepts to non-technical clients and assist in pre-sales conversations.

• Strong proficiency in SQL, Python, and advanced Excel for data profiling, ad-hoc analysis, and identifying hidden structural anomalies in large datasets.

• An extreme attention to detail and a hard-working, proactive attitude. You don't just wait for the pipeline to finish; you actively hunt for edge cases where the rules or LLMs might fail.

• While you don't need to build foundational ML models, you must deeply understand how to interact with LLMs, refine prompts, and adjust deterministic if/then business logic.

• Nice to haves: Previous experience sitting in on sales calls, conducting software demonstrations,

  or managing client POCs (Proof of Concepts); Background in MRO, supply chain, or industrial data (understanding what "good" data looks like in these specific industries).