Senior Consultant – AI Transformation & Decisioning (Legal Environment)
⚲ Wrocław
18 480 - 25 200 PLN (B2B)
Wymagania
- Machine learning
- Use cases
- AI
- Data analysis
- Stakeholder management
- Azure Data Lake (nice to have)
- Python (nice to have)
- SQL (nice to have)
Opis stanowiska
O projekcie:
Project description:
The project focuses on supporting complex data, process, and AI transformation programmes within legal or regulatory environments (e.g. EFSA context). The role involves designing and delivering AI-enabled solutions that enhance decision-making, automate processes, and improve efficiency while ensuring compliance with legal, regulatory, and governance frameworks. The position acts as a bridge between business, legal, data, and technology stakeholders, translating business and legal requirements into scalable AI-driven solutions.
Tech stack:- Microsoft Azure AI Services (Azure OpenAI, Cognitive Services)- Machine Learning frameworks (conceptual or hands-on exposure)- Data platforms (Azure Data Lake, Synapse, Databricks – nice to have)- Search & retrieval technologies (vector search, RAG architectures)- Azure DevOps / Jira (Agile delivery and backlog management)- Power BI / Excel (data analysis and reporting)- M365 tools (Teams, SharePoint, PowerPoint)- Optional: Python / SQLAbout Spyrosoft
Spyrosoft is an authentic, cutting-edge software engineering company, established in 2016. In 2021 and 2022, we were among the fastest growing technology companies in Europe, according to the Financial Times. We were founded by a group of tech experts with established backgrounds in software engineering, who created an ‘engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships. Having a unique offering, which bridge the gap between technology and business, we specialise in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education and financial services industries.
Wymagania:
- AI-enabled transformation programmes (including GenAI / Machine Learning)- Working in or with legal, regulatory, or compliance-driven environments- Redesigning end-to-end business processes leveraging AI- Eliciting and documenting AI-related requirements and use cases- Delivering AI components into production environments- Integrating AI services within enterprise ecosystems (e.g. Azure-hosted AI, data platforms, vector search)- Conducting data analysis with strong attention to data quality and governance- Modelling complex decision processes combining human and AI inputs- Solid understanding of AI/ML concepts and decision intelligence frameworks- Ability to align AI solutions with legal and regulatory requirements- Strong expertise in process optimisation and intelligent automation- Proven ability to translate business and legal needs into technical solutions- Excellent stakeholder management in complex, multi-stakeholder environments- Strong analytical and problem-solving mindsetNice to have:- Experienced in using AI tools in day-to-day workflow- Experience with data platforms such as Azure Data Lake, Synapse, Databricks- Knowledge of Python or SQL
Codzienne zadania:
- Drive AI-enabled transformation initiatives in complex, regulated environments
- Elicit, analyse, and document AI use cases, requirements, and business needs (including legal and compliance aspects)
- Lead end-to-end process redesign with integrated AI capabilities
- Design and support implementation of decision intelligence models combining human judgment and AI outputs
- Contribute to delivery and deployment of AI components into production environments
- Ensure integration of AI services within enterprise architectures (Azure AI, data platforms, vector search)
- Perform data-driven analysis with focus on data quality, traceability, and compliance
- Collaborate with multi-disciplinary stakeholders (legal, business, IT, data, external providers)
- Ensure compliance with governance, security, legal, and enterprise architecture standards
- Support business analysis activities within broader transformation initiatives
Project description:
The project focuses on supporting complex data, process, and AI transformation programmes within legal or regulatory environments (e.g. EFSA context). The role involves designing and delivering AI-enabled solutions that enhance decision-making, automate processes, and improve efficiency while ensuring compliance with legal, regulatory, and governance frameworks. The position acts as a bridge between business, legal, data, and technology stakeholders, translating business and legal requirements into scalable AI-driven solutions.
Tech stack:- Microsoft Azure AI Services (Azure OpenAI, Cognitive Services)- Machine Learning frameworks (conceptual or hands-on exposure)- Data platforms (Azure Data Lake, Synapse, Databricks – nice to have)- Search & retrieval technologies (vector search, RAG architectures)- Azure DevOps / Jira (Agile delivery and backlog management)- Power BI / Excel (data analysis and reporting)- M365 tools (Teams, SharePoint, PowerPoint)- Optional: Python / SQLAbout Spyrosoft
Spyrosoft is an authentic, cutting-edge software engineering company, established in 2016. In 2021 and 2022, we were among the fastest growing technology companies in Europe, according to the Financial Times. We were founded by a group of tech experts with established backgrounds in software engineering, who created an ‘engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships. Having a unique offering, which bridge the gap between technology and business, we specialise in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education and financial services industries.
Wymagania:
- AI-enabled transformation programmes (including GenAI / Machine Learning)- Working in or with legal, regulatory, or compliance-driven environments- Redesigning end-to-end business processes leveraging AI- Eliciting and documenting AI-related requirements and use cases- Delivering AI components into production environments- Integrating AI services within enterprise ecosystems (e.g. Azure-hosted AI, data platforms, vector search)- Conducting data analysis with strong attention to data quality and governance- Modelling complex decision processes combining human and AI inputs- Solid understanding of AI/ML concepts and decision intelligence frameworks- Ability to align AI solutions with legal and regulatory requirements- Strong expertise in process optimisation and intelligent automation- Proven ability to translate business and legal needs into technical solutions- Excellent stakeholder management in complex, multi-stakeholder environments- Strong analytical and problem-solving mindsetNice to have:- Experienced in using AI tools in day-to-day workflow- Experience with data platforms such as Azure Data Lake, Synapse, Databricks- Knowledge of Python or SQL
Codzienne zadania:
- Drive AI-enabled transformation initiatives in complex, regulated environments
- Elicit, analyse, and document AI use cases, requirements, and business needs (including legal and compliance aspects)
- Lead end-to-end process redesign with integrated AI capabilities
- Design and support implementation of decision intelligence models combining human judgment and AI outputs
- Contribute to delivery and deployment of AI components into production environments
- Ensure integration of AI services within enterprise architectures (Azure AI, data platforms, vector search)
- Perform data-driven analysis with focus on data quality, traceability, and compliance
- Collaborate with multi-disciplinary stakeholders (legal, business, IT, data, external providers)
- Ensure compliance with governance, security, legal, and enterprise architecture standards
- Support business analysis activities within broader transformation initiatives
🔍 Dekoder Ogłoszenia
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The position acts as a bridge between business, legal, data, and technology stakeholders, translating business and legal requirements into scalable AI-driven solutions.
Oczekuje się od Ciebie nie tylko technicznych umiejętności, ale także zdolności do komunikacji i negocjacji z różnymi działami, co może oznaczać dużo spotkań i zarządzania oczekiwaniami.
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Machine Learning frameworks (conceptual or hands-on exposure)
Może oznaczać, że nie jest wymagane głębokie, praktyczne doświadczenie w ML, a jedynie ogólna wiedza lub umiejętność zrozumienia koncepcji.
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Data platforms (Azure Data Lake, Synapse, Databricks – nice to have)
Choć wymienione jako 'nice to have', brak doświadczenia w tych obszarach może ograniczyć Twoje możliwości w projekcie, jeśli staną się one kluczowe.
🔴
authentic, cutting-edge software engineering company
Może sugerować, że firma jest innowacyjna, ale również może oznaczać brak ugruntowanych procesów i potrzebę ciągłego dostosowywania się do nowych technologii.
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engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships
Podkreśla kulturę opartą na współpracy i pasji, co jest pozytywne, ale może też oznaczać mniej formalną strukturę i większą odpowiedzialność indywidualną.